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rename .story_kit directory to .storkit and update all references

Browse Source 
Renames the config directory and updates 514 references across 42 Rust
source files, plus CLAUDE.md, .gitignore, Makefile, script/release,
and .mcp.json files. All 1205 tests pass.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Dave
2026-03-20 11:34:53 +00:00
parent 375277f86e
commit 9581e5d51a
406 changed files with 531 additions and 530 deletions
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---
name: "Gate pipeline transitions on ensure_acceptance"
---
# Story 169: Gate pipeline transitions on ensure_acceptance
## User Story
As a project owner, I want story progression to be blocked unless ensure_acceptance passes, so that agents can't skip the testing workflow.
## Acceptance Criteria
- [ ] move_story_to_merge rejects stories that haven't passed ensure_acceptance
- [ ] accept_story rejects stories that haven't passed ensure_acceptance
- [ ] Rejection returns a clear error message telling the agent what's missing
- [ ] Existing passing stories (all criteria checked, tests recorded) still flow through normally
## Out of Scope
- TBD

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name: "Upgrade libsqlite3-sys"
---
# Refactor 260: Upgrade libsqlite3-sys
## Description
Upgrade the `libsqlite3-sys` dependency from `0.35.0` to `0.37.0`. The crate is used with `features = ["bundled"]` for static builds.
## Version Notes
- Current: `libsqlite3-sys 0.35.0` (pinned transitively by `matrix-sdk 0.16.0` → `matrix-sdk-sqlite` → `rusqlite 0.37.x`)
- Target: `libsqlite3-sys 0.37.0`
- Latest upstream rusqlite: `0.39.0`
- **Blocker**: `matrix-sdk 0.16.0` pins `rusqlite 0.37.x` which pins `libsqlite3-sys 0.35.0`. A clean upgrade requires either waiting for matrix-sdk to bump their rusqlite dep, or upgrading matrix-sdk itself.
- **Reverted 2026-03-17**: A previous coder vendored the entire rusqlite crate with a fake `0.37.99` version and patched its libsqlite3-sys dep. This was too hacky — reverted to clean `0.35.0`.
## Acceptance Criteria
- [ ] `libsqlite3-sys` is upgraded to `0.37.0` via a clean dependency path (no vendored forks)
- [ ] `cargo build` succeeds
- [ ] All tests pass
- [ ] No `[patch.crates-io]` hacks or vendored crates

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---
name: "Evaluate Docker/OrbStack for agent isolation and resource limiting"
agent: coder-opus
---
# Spike 329: Evaluate Docker/OrbStack for agent isolation and resource limiting
## Question
Investigate running the entire storkit system (server, Matrix bot, agents, web UI) inside a single Docker container, using OrbStack as the macOS runtime for better performance. The goal is to isolate storkit from the host machine — not to isolate agents from each other.
Currently storkit runs as bare processes on the host with full filesystem and network access. A single container would provide:
1. **Host isolation** — storkit can't touch anything outside the container
2. **Clean install/uninstall** — `docker run` to start, `docker rm` to remove
3. **Reproducible environment** — same container works on any machine
4. **Distributable product** — `docker pull storkit` for new users
5. **Resource limits** — cap total CPU/memory for the whole system
## Architecture
```
Docker Container (single)
├── storkit server
│ ├── Matrix bot
│ ├── WhatsApp webhook
│ ├── Slack webhook
│ ├── Web UI
│ └── MCP server
├── Agent processes (coder-1, coder-2, coder-opus, qa, mergemaster)
├── Rust toolchain + Node.js + Claude Code CLI
└── /workspace (bind-mounted project repo from host)
```
## Key questions to answer:
- **Performance**: How much slower are cargo builds inside the container on macOS? Compare Docker Desktop vs OrbStack for bind-mounted volumes.
- **Dockerfile**: What's the minimal image for the full stack? Rust toolchain + Node.js + Claude Code CLI + cargo-nextest + git.
- **Bind mounts**: The project repo is bind-mounted from the host. Any filesystem performance concerns with OrbStack?
- **Networking**: Container exposes web UI port (3000). Matrix/WhatsApp/Slack connect outbound. Any issues?
- **API key**: Pass ANTHROPIC_API_KEY as env var to the container.
- **Git**: Git operations happen inside the container on the bind-mounted repo. Commits are visible on the host immediately.
- **Cargo cache**: Use a named Docker volume for ~/.cargo/registry so dependencies persist across container restarts.
- **Claude Code state**: Where does Claude Code store its session data? Needs to persist or be in a volume.
- **OrbStack vs Docker Desktop**: Is OrbStack required for acceptable performance, or does Docker Desktop work too?
- **Server restart**: Does `rebuild_and_restart` work inside a container (re-exec with new binary)?
## Deliverable:
A proof-of-concept Dockerfile, docker-compose.yml, and a short write-up with findings and performance benchmarks.
## Hypothesis
- TBD
## Timebox
- TBD
## Investigation Plan
- TBD
## Findings
- TBD
## Recommendation
- TBD

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name: "Abstract agent runtime to support non-Claude-Code backends"
---
# Refactor 343: Abstract agent runtime to support non-Claude-Code backends
## Current State
- TBD
## Desired State
Currently agent spawning is tightly coupled to Claude Code CLI — agents are spawned as PTY processes running the `claude` binary. To support ChatGPT and Gemini as agent backends, we need to abstract the agent runtime.
The agent pool currently does:
1. Spawn `claude` CLI process via portable-pty
2. Stream JSON events from stdout
3. Parse tool calls, text output, thinking traces
4. Wait for process exit, run gates
This needs to become a trait so different backends can be plugged in:
- Claude Code (existing) — spawns `claude` CLI, parses JSON stream
- OpenAI API — calls ChatGPT via API with tool definitions, manages conversation loop
- Gemini API — calls Gemini via API with tool definitions, manages conversation loop
The key abstraction is: an agent runtime takes a prompt + tools and produces a stream of events (text output, tool calls, completion). The existing PTY/Claude Code logic becomes one implementation of this trait.
## Acceptance Criteria
- [ ] Define an AgentRuntime trait with methods for: start, stream_events, stop, get_status
- [ ] ClaudeCodeRuntime implements the trait using existing PTY spawning logic
- [ ] Agent pool uses the trait instead of directly spawning Claude Code
- [ ] Runtime selection is configurable per agent in project.toml (e.g. runtime = 'claude-code')
- [ ] All existing Claude Code agent functionality preserved
- [ ] Event stream format is runtime-agnostic (text, tool_call, thinking, done)
- [ ] Token usage tracking works across runtimes
## Out of Scope
- TBD

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---
name: "ChatGPT agent backend via OpenAI API"
---
# Story 344: ChatGPT agent backend via OpenAI API
## User Story
As a project owner, I want to run agents using ChatGPT (GPT-4o, o3, etc.) via the OpenAI API, so that I can use OpenAI models for coding tasks alongside Claude.
## Acceptance Criteria
- [ ] Implement OpenAiRuntime using the AgentRuntime trait from refactor 343
- [ ] Supports GPT-4o and o3 models via the OpenAI chat completions API
- [ ] Manages a conversation loop: send prompt + tool definitions, execute tool calls, continue until done
- [ ] Agents connect to storkit's MCP server for all tool operations — no custom file/bash tools needed
- [ ] MCP tool definitions are converted to OpenAI function calling format
- [ ] Configurable in project.toml: runtime = 'openai', model = 'gpt-4o'
- [ ] OPENAI_API_KEY passed via environment variable
- [ ] Token usage tracked and logged to token_usage.jsonl
- [ ] Agent output streams to the same event system (web UI, bot notifications)
## Out of Scope
- TBD

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---
name: "Gemini agent backend via Google AI API"
---
# Story 345: Gemini agent backend via Google AI API
## User Story
As a project owner, I want to run agents using Gemini (2.5 Pro, etc.) via the Google AI API, so that I can use Google models for coding tasks alongside Claude and ChatGPT.
## Acceptance Criteria
- [ ] Implement GeminiRuntime using the AgentRuntime trait from refactor 343
- [ ] Supports Gemini 2.5 Pro and other Gemini models via the Google AI generativeai API
- [ ] Manages a conversation loop: send prompt + tool definitions, execute tool calls, continue until done
- [ ] Agents connect to storkit's MCP server for all tool operations — no custom file/bash tools needed
- [ ] MCP tool definitions are converted to Gemini function calling format
- [ ] Configurable in project.toml: runtime = 'gemini', model = 'gemini-2.5-pro'
- [ ] GOOGLE_AI_API_KEY passed via environment variable
- [ ] Token usage tracked and logged to token_usage.jsonl
- [ ] Agent output streams to the same event system (web UI, bot notifications)
## Out of Scope
- TBD

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name: "MCP tools for code search (grep and glob)"
---
# Story 348: MCP tools for code search (grep and glob)
## User Story
As a non-Claude agent connected via MCP, I want search tools so that I can find files and search code contents in my worktree.
## Acceptance Criteria
- [ ] grep tool — searches file contents with regex support, returns matching lines with context
- [ ] glob tool — finds files by pattern (e.g. '**/*.rs')
- [ ] Both scoped to the agent's worktree
- [ ] grep supports output modes: content (matching lines), files_with_matches (just paths), count
- [ ] grep supports context lines (-A, -B, -C)
- [ ] Results limited to prevent overwhelming the LLM context
## Out of Scope
- TBD

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name: "MCP tools for git operations"
---
# Story 349: MCP tools for git operations
## User Story
As a non-Claude agent connected via MCP, I want git tools so that I can check status, stage files, commit changes, and view history in my worktree.
## Acceptance Criteria
- [ ] git_status tool — returns working tree status (staged, unstaged, untracked files)
- [ ] git_diff tool — returns diff output, supports staged/unstaged/commit range
- [ ] git_add tool — stages files by path
- [ ] git_commit tool — commits staged changes with a message
- [ ] git_log tool — returns commit history with configurable count and format
- [ ] All operations run in the agent's worktree
- [ ] Cannot push, force-push, or modify remote — server handles that
## Out of Scope
- TBD

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---
name: "MCP tool for code definitions lookup"
---
# Story 350: MCP tool for code definitions lookup
## User Story
As a non-Claude agent connected via MCP, I want a code intelligence tool so that I can find function, struct, and type definitions without grepping through all files.
## Acceptance Criteria
- [ ] get_definitions tool — finds function/struct/enum/type/class definitions by name or pattern
- [ ] Supports Rust (fn, struct, enum, impl, trait) and TypeScript (function, class, interface, type) at minimum
- [ ] Returns file path, line number, and the definition signature
- [ ] Scoped to the agent's worktree
- [ ] Faster than grepping — uses tree-sitter or regex-based parsing
## Out of Scope
- TBD

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---
name: Agent Security and Sandboxing
---
# Story 34: Agent Security and Sandboxing
## User Story
**As a** supervisor orchestrating multiple autonomous agents,
**I want to** constrain what each agent can access and do,
**So that** agents can't escape their worktree, damage shared state, or perform unintended actions.
## Acceptance Criteria
- [ ] Agent creation accepts an `allowed_tools` list to restrict Claude Code tool access per agent.
- [ ] Agent creation accepts a `disallowed_tools` list as an alternative to allowlisting.
- [ ] Agents without Bash access can still perform useful coding work (Read, Edit, Write, Glob, Grep).
- [ ] Investigate replacing direct Bash/shell access with Rust-implemented tool proxies that enforce boundaries:
- Scoped `exec_shell` that only runs allowlisted commands (e.g., `cargo test`, `npm test`) within the agent's worktree.
- Scoped `read_file` / `write_file` that reject paths outside the agent's worktree root.
- Scoped `git` operations that only work within the agent's worktree.
- [ ] Evaluate `--max-turns` and `--max-budget-usd` as safety limits for runaway agents.
- [ ] Document the trust model: what the supervisor controls vs what agents can do autonomously.
## Questions to Explore
- Can we use MCP (Model Context Protocol) to expose our Rust-implemented tools to Claude Code, replacing its built-in Bash/filesystem tools with scoped versions?
- What's the right granularity for shell allowlists — command-level (`cargo test`) or pattern-level (`cargo *`)?
- Should agents have read access outside their worktree (e.g., to reference shared specs) but write access only within it?
- Is OS-level sandboxing (Docker, macOS sandbox profiles) worth the complexity for a personal tool?
## Out of Scope
- Multi-user authentication or authorization (single-user personal tool).
- Network-level isolation between agents.
- Encrypting agent communication channels (all local).

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---
name: Live Test Gate Updates
---
# Story 57: Live Test Gate Updates
## User Story
As a user, I want the Gate and Todo panels to update automatically when tests are recorded or acceptance is checked, so I can see progress without manually refreshing.
## Acceptance Criteria
- [ ] Server broadcasts a `{"type": "notification", "topic": "tests"}` event over `/ws` when tests are recorded, acceptance is checked, or coverage is collected
- [ ] GatePanel auto-refreshes its data when it receives a `tests` notification
- [ ] TodoPanel auto-refreshes its data when it receives a `tests` notification
- [ ] Manual refresh buttons continue to work
- [ ] Panels do not flicker or lose scroll position on auto-refresh
- [ ] End-to-end test: record test results via MCP, verify Gate panel updates without manual refresh

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name: "Fetch real context window size from Anthropic models API"
---
# Story 90: Fetch real context window size from Anthropic models API
## User Story
As a user chatting with a Claude model, I want the context remaining indicator to show the actual context window size for the selected model (fetched from the Anthropic API) instead of a hardcoded value, so that the indicator is accurate across all current and future models.
## Acceptance Criteria
- [ ] Backend AnthropicModelInfo struct deserializes the context_window field from the Anthropic /v1/models response
- [ ] Backend /anthropic/models endpoint returns both model ID and context window size to the frontend
- [ ] Frontend uses the real context window size from the API response instead of the hardcoded getContextWindowSize map for Anthropic models
- [ ] Context indicator in ChatHeader displays the correct percentage based on the real context window size
- [ ] Hardcoded fallback remains for Ollama/local models that don't provide context window metadata
## Out of Scope
- TBD

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name: "Consolidate chat transports into a chat module with transport submodules"
---
# Refactor 330: Consolidate chat transports into a chat module with transport submodules
## Current State
- TBD
## Desired State
The chat/transport code is scattered across the codebase: transport.rs at the top level, matrix/ as a module with transport-agnostic command logic baked in, whatsapp.rs and slack.rs as top-level files. Consolidate into a unified chat/ module where common code lives at the top level and only transport-specific details live in submodules.
Target structure:
```
server/src/chat/
├── mod.rs — ChatTransport trait, shared types, re-exports
├── commands/ — command registry and handlers (moved OUT of matrix/)
│ ├── mod.rs — BotCommand, CommandContext, CommandDispatch, try_handle_command
│ ├── status.rs — handle_status, build_pipeline_status
│ ├── cost.rs — handle_cost
│ ├── help.rs — handle_help
│ ├── git.rs — handle_git
│ ├── show.rs — handle_show
│ ├── overview.rs — handle_overview
│ ├── ambient.rs — handle_ambient
│ └── delete.rs — handle_delete
├── htop.rs — htop dashboard logic (moved OUT of matrix/ — works on any transport)
├── matrix/ — Matrix-specific: bot.rs, transport_impl.rs, config, notifications
├── whatsapp.rs — WhatsApp-specific: webhook, transport impl, 24h window
└── slack.rs — Slack-specific: webhook, transport impl, slash commands
```
The key insight: commands/, htop, and the ChatTransport trait are transport-agnostic. They currently live inside matrix/ but have nothing to do with Matrix. Only the actual Matrix SDK calls (sending messages, typing indicators, message editing, E2E encryption) are Matrix-specific.
## Acceptance Criteria
- [ ] transport.rs moved into chat/mod.rs (ChatTransport trait and shared types)
- [ ] commands/ moved from matrix/commands/ to chat/commands/ — no Matrix imports in command handlers
- [ ] htop.rs moved from matrix/htop.rs to chat/htop.rs — uses ChatTransport trait, not Matrix types
- [ ] whatsapp.rs moved to chat/whatsapp.rs
- [ ] slack.rs moved to chat/slack.rs
- [ ] matrix/ moved to chat/matrix/ — only contains Matrix-specific code (bot message handler, SDK calls, transport_impl, config)
- [ ] matrix/bot.rs no longer contains command dispatch logic — delegates to chat/commands/
- [ ] All imports updated throughout the codebase
- [ ] All existing tests pass
- [ ] No public API changes from the perspective of main.rs and other modules
## Out of Scope
- TBD

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name: "Bot start command to start a coder on a story"
---
# Story 331: Bot start command to start a coder on a story
## User Story
As a project owner in a chat room, I want to type "{bot_name} start {story_number}" to start a coder on a story, so that I can kick off work without needing the MCP tools or web UI.
## Acceptance Criteria
- [ ] '{bot_name} start {number}' finds the story and starts the default coder agent on it
- [ ] '{bot_name} start {number} opus' starts coder-opus specifically
- [ ] Returns confirmation with agent name and story title
- [ ] Returns error if story not found or all coders busy
- [ ] Moves story from backlog to current if needed
- [ ] Registered in the command registry so it appears in help output
- [ ] Handled at bot level without LLM invocation
## Out of Scope
- TBD

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name: "Bot assign command to assign a specific agent to a story"
---
# Story 332: Bot assign command to assign a specific agent to a story
## User Story
As a project owner in a chat room, I want to type "{bot_name} assign {story_number} {agent_name}" to assign a specific agent to a story, so that I can control which agent works on which story from chat.
## Acceptance Criteria
- [ ] '{bot_name} assign {number} {agent}' assigns the specified agent to the story (e.g. 'timmy assign 315 coder-opus')
- [ ] Stops any currently running agent on that story before assigning the new one
- [ ] Updates the story's front matter with agent: {agent_name}
- [ ] Starts the agent immediately
- [ ] Returns confirmation with agent name and story title
- [ ] Returns error if agent name is not valid or story not found
- [ ] Registered in the command registry so it appears in help output
- [ ] Handled at bot level without LLM invocation
## Out of Scope
- TBD

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name: "Bot stop command to stop an agent on a story"
---
# Story 333: Bot stop command to stop an agent on a story
## User Story
As a project owner in a chat room, I want to type "{bot_name} stop {story_number}" to stop the running agent on a story, so that I can halt work from chat without MCP tools.
## Acceptance Criteria
- [ ] '{bot_name} stop {number}' stops the running agent on that story
- [ ] Returns confirmation with agent name, story title, and what stage it was in
- [ ] Returns friendly message if no agent is running on that story
- [ ] Registered in the command registry so it appears in help output
- [ ] Handled at bot level without LLM invocation
## Out of Scope
- TBD

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name: "Bot move command to move stories between pipeline stages"
---
# Story 334: Bot move command to move stories between pipeline stages
## User Story
As a project owner in a chat room, I want to type "{bot_name} move {story_number} {stage}" to move a story between pipeline stages, so that I can manage the pipeline from chat.
## Acceptance Criteria
- [ ] '{bot_name} move {number} {stage}' moves the story to the specified stage (backlog, current, done)
- [ ] Uses the existing move_story MCP tool under the hood
- [ ] Returns confirmation with story title, old stage, and new stage
- [ ] Returns error if story not found or invalid stage
- [ ] Registered in the command registry so it appears in help output
- [ ] Handled at bot level without LLM invocation
## Out of Scope
- TBD

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---
name: "Bot rebuild command to trigger server rebuild and restart"
---
# Story 335: Bot rebuild command to trigger server rebuild and restart
## User Story
As a project owner in a chat room, I want to type "{bot_name} rebuild" to rebuild and restart the server, so that I can deploy changes from my phone without terminal access.
## Acceptance Criteria
- [ ] '{bot_name} rebuild' triggers the rebuild_and_restart MCP tool
- [ ] Bot sends a confirmation message before rebuilding
- [ ] Handled at bot level — intercepts the command before forwarding to LLM
- [ ] Registered in the command registry so it appears in help output
## Out of Scope
- TBD

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---
name: "Web UI button to start a coder on a story"
---
# Story 336: Web UI button to start a coder on a story
## User Story
As a project owner using the web UI, I want to click a button on a work item to start a coder on it, so that I can kick off work without using the terminal or chat bot.
## Acceptance Criteria
- [ ] Start button visible on work items in backlog and current stages
- [ ] Clicking start assigns the default coder and moves the story to current if needed
- [ ] Option to select a specific agent (dropdown: coder-1, coder-2, coder-opus)
- [ ] Button disabled when all coders are busy (shows tooltip explaining why)
- [ ] UI updates immediately to show the assigned agent
## Out of Scope
- TBD

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name: "Web UI button to stop an agent on a story"
---
# Story 337: Web UI button to stop an agent on a story
## User Story
As a project owner using the web UI, I want to click a button on a work item to stop its running agent, so that I can halt work without using the terminal or chat bot.
## Acceptance Criteria
- [ ] Stop button visible on work items that have a running agent
- [ ] Clicking stop kills the agent and shows confirmation
- [ ] Button only appears when an agent is actively running
- [ ] UI updates immediately to reflect the agent is stopped
## Out of Scope
- TBD

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name: "Web UI button to move stories between pipeline stages"
---
# Story 338: Web UI button to move stories between pipeline stages
## User Story
As a project owner using the web UI, I want to drag or click to move stories between pipeline stages, so that I can manage the pipeline visually.
## Acceptance Criteria
- [ ] Move buttons or dropdown on each work item to change stage (backlog, current, done)
- [ ] Uses the existing move_story MCP tool under the hood
- [ ] Shows confirmation with old and new stage
- [ ] UI updates immediately to reflect the move
- [ ] Prevents invalid moves (e.g. moving to QA or merge without an agent)
## Out of Scope
- TBD

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name: "Web UI agent assignment dropdown on work items"
---
# Story 339: Web UI agent assignment dropdown on work items
## User Story
As a project owner using the web UI, I want to select which agent to assign to a work item from a dropdown, so that I can control agent assignments visually.
## Acceptance Criteria
- [ ] Agent dropdown visible in expanded work item detail panel
- [ ] Shows available agents filtered by appropriate stage (coders for current, QA for qa, mergemaster for merge)
- [ ] Selecting an agent stops any current agent and starts the new one
- [ ] Updates the story front matter with the agent assignment
- [ ] Shows agent status (running, idle) in the dropdown
## Out of Scope
- TBD

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name: "Web UI rebuild and restart button"
---
# Story 340: Web UI rebuild and restart button
## User Story
As a project owner using the web UI, I want a rebuild and restart button, so that I can deploy changes without terminal access.
## Acceptance Criteria
- [ ] Rebuild button in the web UI header or settings area
- [ ] Shows confirmation dialog before triggering rebuild
- [ ] Triggers the rebuild_and_restart MCP tool
- [ ] Shows build progress or status indicator
- [ ] Handles reconnection after server restarts
## Out of Scope
- TBD

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name: "Web UI button to delete a story from the pipeline"
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# Story 342: Web UI button to delete a story from the pipeline
## User Story
As a project owner using the web UI, I want a delete button on work items to remove them from the pipeline, so that I can clean up obsolete or duplicate stories visually.
## Acceptance Criteria
- [ ] Delete button visible on work items in all pipeline stages
- [ ] Shows confirmation dialog before deleting (story title shown for clarity)
- [ ] Stops any running agent on the story before deleting
- [ ] Removes the worktree if one exists
- [ ] Deletes the story file and commits to git
- [ ] UI updates immediately to remove the item from the board
- [ ] Uses an appropriate API endpoint (new or existing)
## Out of Scope
- TBD

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name: "MCP tools for file operations (read, write, edit, list)"
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# Story 346: MCP tools for file operations (read, write, edit, list)
## User Story
As a non-Claude agent connected via MCP, I want file operation tools so that I can read, write, and edit code in my worktree.
## Acceptance Criteria
- [ ] read_file tool — reads file contents, supports offset/limit for large files
- [ ] write_file tool — writes/creates a file at a given path
- [ ] edit_file tool — replaces a string in a file (old_string/new_string like Claude Code's Edit)
- [ ] list_files tool — glob pattern matching to find files in the worktree
- [ ] All operations scoped to the agent's worktree path for safety
- [ ] Returns clear errors for missing files, permission issues, etc.
## Out of Scope
- TBD

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name: "MCP tool for shell command execution"
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# Story 347: MCP tool for shell command execution
## User Story
As a non-Claude agent connected via MCP, I want a shell command tool so that I can run cargo build, npm test, and other commands in my worktree.
## Acceptance Criteria
- [ ] run_command tool — executes a bash command and returns stdout/stderr/exit_code
- [ ] Command runs in the agent's worktree directory
- [ ] Supports timeout parameter (default 120s, max 600s)
- [ ] Sandboxed to worktree — cannot cd outside or access host paths
- [ ] Returns streaming output for long-running commands
- [ ] Dangerous commands blocked (rm -rf /, etc.)
## Out of Scope
- TBD

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name: "Bot reset command to clear conversation context"
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# Story 351: Bot reset command to clear conversation context
## User Story
As a project owner in a chat room, I want to type "{bot_name} reset" to drop the current Claude Code session and start fresh, so that I can reduce token usage when context gets bloated without restarting the server.
## Acceptance Criteria
- [ ] '{bot_name} reset' kills the current Claude Code session
- [ ] A new session starts immediately with clean context
- [ ] Memories persist via the file system (auto-memory directory is unchanged)
- [ ] Bot confirms the reset with a short message
- [ ] Registered in the command registry so it appears in help output
- [ ] Handled at bot level without LLM invocation
## Out of Scope
- TBD

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name: "Ambient on/off command not intercepted by bot after refactors"
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# Bug 352: Ambient on/off command not intercepted by bot after refactors
## Description
The ambient on/off bot command stopped being intercepted by the bot after the recent refactors (328 split commands.rs into modules, 330 consolidated chat transports into chat/ module). Messages like "timmy ambient off", "ambient off", and "ambient on" are being forwarded to the LLM instead of being handled at the bot level. The ambient toggle was previously handled in bot.rs before the command registry dispatch — it may not have been properly wired up after the code was moved to the chat/ module structure.
## How to Reproduce
1. Type "timmy ambient off" in a Matrix room where ambient mode is on
2. Observe that the message is forwarded to Claude instead of being intercepted
3. Same for "timmy ambient on", "ambient off", "ambient on"
## Actual Result
Ambient toggle commands are forwarded to the LLM as regular messages.
## Expected Result
Ambient toggle commands should be intercepted at the bot level and toggle ambient mode without invoking the LLM, with a confirmation message sent directly.
## Acceptance Criteria
- [ ] 'timmy ambient on' toggles ambient mode on and sends confirmation without LLM invocation
- [ ] 'timmy ambient off' toggles ambient mode off and sends confirmation without LLM invocation
- [ ] Ambient toggle works after refactors 328 and 330
- [ ] Ambient state persists in bot.toml as before

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name: "Add party emoji to done stage notification messages"
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# Story 353: Add party emoji to done stage notification messages
## User Story
As a project owner, I want to see a party emoji in the Matrix/chat notification when a story moves to done, so that completions feel celebratory.
## Acceptance Criteria
- [ ] Stage notification for done includes a party emoji (e.g. 🎉)
- [ ] Only the done stage gets the emoji — other stage transitions stay as they are
- [ ] Works across all chat transports (Matrix, WhatsApp, Slack)
## Out of Scope
- TBD

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name: Project Selection & Read Verification
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# Story: Project Selection & Read Verification
## User Story
**As a** User
**I want to** select a local folder on my computer as the "Target Project"
**So that** the assistant knows which codebase to analyze and work on.
## Acceptance Criteria
* [ ] UI has an "Open Project" button.
* [ ] Clicking the button opens the native OS folder picker.
* [ ] Upon selection, the UI displays the selected path.
* [ ] The system verifies the folder exists and is readable.
* [ ] The application state persists the "Current Project" (in memory is fine for now).
## Out of Scope
* Persisting the selection across app restarts (save that for later).
* Scanning the file tree (just verify the root exists).
* Git validation (we'll assume any folder is valid for now).

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name: Core Agent Tools (The Hands)
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# Story: Core Agent Tools (The Hands)
## User Story
**As an** Agent
**I want to** be able to read files, list directories, search content, and execute shell commands
**So that** I can autonomously explore and modify the target project.
## Acceptance Criteria
* [ ] Rust Backend: Implement `read_file(path)` command (scoped to project).
* [ ] Rust Backend: Implement `write_file(path, content)` command (scoped to project).
* [ ] Rust Backend: Implement `list_directory(path)` command.
* [ ] Rust Backend: Implement `exec_shell(command, args)` command.
* [ ] Must enforce allowlist (git, cargo, npm, etc).
* [ ] Must run in project root.
* [ ] Rust Backend: Implement `search_files(query, globs)` using `ignore` crate.
* [ ] Frontend: Expose these as tools to the (future) LLM interface.
## Out of Scope
* The LLM Chat UI itself (connecting these to a visual chat window comes later).
* Complex git merges (simple commands only).

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name: The Agent Brain (Ollama Integration)
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# Story: The Agent Brain (Ollama Integration)
## User Story
**As a** User
**I want to** connect the Assistant to a local Ollama instance
**So that** I can chat with the Agent and have it execute tools without sending data to the cloud.
## Acceptance Criteria
* [ ] Backend: Implement `ModelProvider` trait/interface.
* [ ] Backend: Implement `OllamaProvider` (POST /api/chat).
* [ ] Backend: Implement `chat(message, history, provider_config)` command.
* [ ] Must support passing Tool Definitions to Ollama (if model supports it) or System Prompt instructions.
* [ ] Must parse Tool Calls from the response.
* [ ] Frontend: Settings Screen to toggle "Ollama" and set Model Name (default: `llama3`).
* [ ] Frontend: Chat Interface.
* [ ] Message History (User/Assistant).
* [ ] Tool Call visualization (e.g., "Running git status...").
## Out of Scope
* Remote Providers (Anthropic/OpenAI) - Future Story.
* Streaming responses (wait for full completion for MVP).
* Complex context window management (just send full history for now).

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name: Ollama Model Detection
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# Story: Ollama Model Detection
## User Story
**As a** User
**I want to** select my Ollama model from a dropdown list of installed models
**So that** I don't have to manually type (and potentially mistype) the model names.
## Acceptance Criteria
* [ ] Backend: Implement `get_ollama_models()` command.
* [ ] Call `GET /api/tags` on the Ollama instance.
* [ ] Parse the JSON response to extracting model names.
* [ ] Frontend: Replace the "Ollama Model" text input with a `<select>` dropdown.
* [ ] Frontend: Populate the dropdown on load.
* [ ] Frontend: Handle connection errors gracefully (if Ollama isn't running, show empty or error).
## Out of Scope
* Downloading new models via the UI (pulling).

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name: Persist Project Selection
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# Story: Persist Project Selection
## User Story
**As a** User
**I want** the application to remember the last project I opened
**So that** I don't have to re-select the directory every time I restart the app.
## Acceptance Criteria
* [ ] Backend: Use `tauri-plugin-store` (or simple JSON file) to persist `last_project_path`.
* [ ] Backend: On app startup, check if a saved path exists.
* [ ] Backend: If saved path exists and is valid, automatically load it into `SessionState`.
* [ ] Frontend: On load, check if backend has a project ready. If so, skip selection screen.
* [ ] Frontend: Add a "Close Project" button to clear the state and return to selection screen.
## Out of Scope
* Managing a list of "Recent Projects" (just the last one is fine for now).

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name: Fix UI Responsiveness (Tech Debt)
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# Story: Fix UI Responsiveness (Tech Debt)
## User Story
**As a** User
**I want** the UI to remain interactive and responsive while the Agent is thinking or executing tools
**So that** I don't feel like the application has crashed.
## Context
Currently, the UI locks up or becomes unresponsive during long LLM generations or tool executions. Even though the backend commands are async, the frontend experience degrades.
## Acceptance Criteria
* [ ] Investigate the root cause of the freezing (JS Main Thread blocking vs. Tauri IPC blocking).
* [ ] Implement a "Streaming" architecture for Chat if necessary (getting partial tokens instead of waiting for full response).
* *Note: This might overlap with future streaming stories, but basic responsiveness is the priority here.*
* [ ] Add visual indicators (Spinner/Progress Bar) that animate smoothly during the wait.
* [ ] Ensure the "Stop Generation" button (if added) can actually interrupt the backend task.
## Out of Scope
* Full streaming text (unless that is the only way to fix the freezing).

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name: UI Polish - Sticky Header & Compact Layout
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# Story: UI Polish - Sticky Header & Compact Layout
## User Story
**As a** User
**I want** key controls (Model Selection, Tool Toggle, Project Path) to be visible at all times
**So that** I don't have to scroll up to check my configuration or change settings.
## Acceptance Criteria
* [ ] Frontend: Create a fixed `<Header />` component at the top of the viewport.
* [ ] Frontend: Move "Active Project" display into this header (make it compact/truncated if long).
* [ ] Frontend: Move "Ollama Model" and "Enable Tools" controls into this header.
* [ ] Frontend: Ensure the Chat message list scrolls *under* the header (taking up remaining height).
* [ ] Frontend: Remove the redundant "Active Project" bar from the main workspace area.
## Out of Scope
* Full visual redesign (just layout fixing).
* Settings modal (keep controls inline for now).

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name: Collapsible Tool Outputs
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# Story: Collapsible Tool Outputs
## User Story
**As a** User
**I want** tool outputs (like long file contents or search results) to be collapsed by default
**So that** the chat history remains readable and I can focus on the Agent's reasoning.
## Acceptance Criteria
* [x] Frontend: Render tool outputs inside a `<details>` / `<summary>` component (or custom equivalent).
* [x] Frontend: Default state should be **Closed/Collapsed**.
* [x] Frontend: The summary line should show the Tool Name + minimal args (e.g., "▶ read_file(src/main.rs)").
* [x] Frontend: Clicking the arrow/summary expands to show the full output.
## Out of Scope
* Complex syntax highlighting for tool outputs (plain text/pre is fine).
## Implementation Plan
1. Create a reusable component for displaying tool outputs with collapsible functionality
2. Update the chat message rendering logic to use this component for tool outputs
3. Ensure the summary line displays tool name and minimal arguments
4. Verify that the component maintains proper styling and readability
5. Test expand/collapse functionality across different tool output types
## Related Functional Specs
* Functional Spec: Tool Outputs

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name: Remove Unnecessary Scroll Bars
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# Story: Remove Unnecessary Scroll Bars
## User Story
**As a** User
**I want** the UI to have clean, minimal scrolling without visible scroll bars
**So that** the interface looks polished and doesn't have distracting visual clutter.
## Acceptance Criteria
* [x] Remove or hide the vertical scroll bar on the right side of the chat area
* [x] Remove or hide any horizontal scroll bars that appear
* [x] Maintain scrolling functionality (content should still be scrollable, just without visible bars)
* [x] Consider using overlay scroll bars or auto-hiding scroll bars for better aesthetics
* [x] Ensure the solution works across different browsers (Chrome, Firefox, Safari)
* [x] Verify that long messages and tool outputs still scroll properly
## Out of Scope
* Custom scroll bar designs with fancy styling
* Touch/gesture scrolling improvements for mobile (desktop focus for now)
## Implementation Notes
* Use CSS `scrollbar-width: none` for Firefox
* Use `::-webkit-scrollbar { display: none; }` for Chrome/Safari
* Ensure `overflow: auto` or `overflow-y: scroll` is still applied to maintain scroll functionality
* Test with long tool outputs and chat histories to ensure no layout breaking
## Related Functional Specs
* Functional Spec: UI/UX

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name: System Prompt & Persona
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# Story: System Prompt & Persona
## User Story
**As a** User
**I want** the Agent to behave like a Senior Engineer and know exactly how to use its tools
**So that** it writes high-quality code and doesn't hallucinate capabilities or refuse to edit files.
## Acceptance Criteria
* [ ] Backend: Define a robust System Prompt constant (likely in `src-tauri/src/llm/prompts.rs`).
* [ ] Content: The prompt should define:
* Role: "Senior Software Engineer / Agent".
* Tone: Professional, direct, no fluff.
* Tool usage instructions: "You have access to the local filesystem. Use `read_file` to inspect context before editing."
* Workflow: "When asked to implement a feature, read relevant files first, then write."
* [ ] Backend: Inject this system message at the *start* of every `chat` session sent to the Provider.
## Out of Scope
* User-editable system prompts (future story).

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name: "Test Coverage: http/context.rs to 100%"
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# Story 100: Test Coverage: http/context.rs to 100%
## User Story
As a developer, I want http/context.rs to have 100% test coverage, so that regressions in AppContext helper methods are caught early.
## Acceptance Criteria
- [ ] server/src/http/context.rs reaches 100% line coverage (3 missing lines covered)
- [ ] cargo clippy passes with no warnings
- [ ] cargo test passes with all tests green
- [ ] No changes to production code, only test code added
## Out of Scope
- TBD

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name: "Test Coverage: http/chat.rs to 80%"
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# Story 101: Test Coverage: http/chat.rs to 80%
## User Story
As a developer, I want http/chat.rs to have at least 80% test coverage, so that regressions in the chat HTTP handler are caught early.
## Acceptance Criteria
- [ ] server/src/http/chat.rs reaches at least 80% line coverage (currently 0%, 5 lines total)
- [ ] cargo clippy passes with no warnings
- [ ] cargo test passes with all tests green
- [ ] No changes to production code, only test code added
## Out of Scope
- TBD

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name: "Test Coverage: http/model.rs to 80%"
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# Story 102: Test Coverage: http/model.rs to 80%
## User Story
As a developer, I want http/model.rs to have at least 80% test coverage, so that regressions in model preference get/set handlers are caught early.
## Acceptance Criteria
- [ ] server/src/http/model.rs reaches at least 80% line coverage (currently 0%, 22 lines missed)
- [ ] cargo clippy passes with no warnings
- [ ] cargo test passes with all tests green
- [ ] No changes to production code, only test code added
## Out of Scope
- TBD

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name: "Test Coverage: http/project.rs to 80%"
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# Story 103: Test Coverage: http/project.rs to 80%
## User Story
As a developer, I want http/project.rs to have at least 80% test coverage, so that regressions in project list/open handlers are caught early.
## Acceptance Criteria
- [ ] server/src/http/project.rs reaches at least 80% line coverage (currently 0%, 30 lines missed)
- [ ] cargo clippy passes with no warnings
- [ ] cargo test passes with all tests green
- [ ] No changes to production code, only test code added
## Out of Scope
- TBD

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name: "Test Coverage: io/search.rs to 95%"
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# Story 104: Test Coverage: io/search.rs to 95%
## User Story
As a developer, I want io/search.rs to have at least 95% test coverage, so that regressions in search edge cases are caught early.
## Acceptance Criteria
- [ ] server/src/io/search.rs reaches at least 95% line coverage (currently 89%, 14 lines missed)
- [ ] cargo clippy passes with no warnings
- [ ] cargo test passes with all tests green
- [ ] No changes to production code, only test code added
## Out of Scope
- TBD

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name: "Test Coverage: io/shell.rs to 95%"
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# Story 105: Test Coverage: io/shell.rs to 95%
## User Story
As a developer, I want io/shell.rs to have at least 95% test coverage, so that regressions in shell execution edge cases are caught early.
## Acceptance Criteria
- [ ] server/src/io/shell.rs reaches at least 95% line coverage (currently 84%, 15 lines missed)
- [ ] cargo clippy passes with no warnings
- [ ] cargo test passes with all tests green
- [ ] No changes to production code, only test code added
## Out of Scope
- TBD

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name: "Test Coverage: http/settings.rs to 80%"
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# Story 106: Test Coverage: http/settings.rs to 80%
## User Story
As a developer, I want http/settings.rs to have at least 80% test coverage, so that regressions in settings get/set handlers are caught early.
## Acceptance Criteria
- [ ] server/src/http/settings.rs reaches at least 80% line coverage (currently 59%, 35 lines missed)
- [ ] cargo clippy passes with no warnings
- [ ] cargo test passes with all tests green
- [ ] No changes to production code, only test code added
## Out of Scope
- TBD

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name: "Test Coverage: http/assets.rs to 85%"
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# Story 107: Test Coverage: http/assets.rs to 85%
## User Story
As a developer, I want http/assets.rs to have at least 85% test coverage, so that regressions in static asset serving are caught early.
## Acceptance Criteria
- [ ] server/src/http/assets.rs reaches at least 85% line coverage (currently 70%, 18 lines missed)
- [ ] cargo clippy passes with no warnings
- [ ] cargo test passes with all tests green
- [ ] No changes to production code, only test code added
## Out of Scope
- TBD

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name: "Test Coverage: http/agents.rs to 70%"
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# Story 108: Test Coverage: http/agents.rs to 70%
## User Story
As a developer, I want http/agents.rs to have at least 70% test coverage, so that regressions in REST agent status/control endpoints are caught early.
## Acceptance Criteria
- [ ] server/src/http/agents.rs reaches at least 70% line coverage (currently 38%, 155 lines missed)
- [ ] cargo clippy passes with no warnings
- [ ] cargo test passes with all tests green
- [ ] No changes to production code, only test code added
## Out of Scope
- TBD

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name: "Add test coverage for LozengeFlyContext, SelectionScreen, and ChatHeader components"
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# Story 109: Add test coverage for LozengeFlyContext, SelectionScreen, and ChatHeader components
## User Story
As a developer, I want better test coverage for LozengeFlyContext.tsx, SelectionScreen.tsx, and ChatHeader.tsx, so that regressions are caught early.
## Acceptance Criteria
- [ ] LozengeFlyContext.tsx reaches 100% coverage (currently 98.1%, 5 lines missing)
- [ ] SelectionScreen.tsx reaches 100% coverage (currently 93.5%, 5 lines missing)
- [ ] ChatHeader.tsx reaches 95% coverage (currently 87.7%, 25 lines missing)
- [ ] All vitest tests pass
- [ ] No production code changes are made
## Out of Scope
- TBD

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name: Persist Model Selection
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# Story: Persist Model Selection
## User Story
**As a** User
**I want** the application to remember which LLM model I selected
**So that** I don't have to switch from "llama3" to "deepseek" every time I launch the app.
## Acceptance Criteria
* [ ] Backend/Frontend: Use `tauri-plugin-store` to save the `selected_model` string.
* [ ] Frontend: On mount (after fetching available models), check the store.
* [ ] Frontend: If the stored model exists in the available list, select it.
* [ ] Frontend: When the user changes the dropdown, update the store.
## Out of Scope
* Persisting per-project model settings (global setting is fine for now).

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name: "Add test coverage for api/settings.ts"
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# Story 110: Add test coverage for api/settings.ts
## User Story
As a developer, I want better test coverage for api/settings.ts, so that regressions in the settings API wrapper are caught early.
## Acceptance Criteria
- [ ] api/settings.ts reaches 90% coverage (currently 55%, 18 lines missing)
- [ ] Tests use fetch mocks to exercise all API wrapper functions
- [ ] All vitest tests pass
- [ ] No production code changes are made
## Out of Scope
- TBD

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name: "Add test coverage for api/agents.ts"
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# Story 111: Add test coverage for api/agents.ts
## User Story
As a developer, I want better test coverage for api/agents.ts, so that regressions in the agent API wrapper are caught early.
## Acceptance Criteria
- [ ] api/agents.ts reaches 80% coverage (currently 29.5%, 67 lines missing)
- [ ] Tests use fetch mocks to exercise all agent API wrapper functions
- [ ] All vitest tests pass
- [ ] No production code changes are made
## Out of Scope
- TBD

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name: "Add test coverage for App.tsx"
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# Story 112: Add test coverage for App.tsx
## User Story
As a developer, I want better test coverage for App.tsx, so that regressions in the main application component are caught early.
## Acceptance Criteria
- [ ] App.tsx reaches 85% coverage (currently 73.1%, 43 lines missing)
- [ ] Tests cover additional integration-style scenarios for the main app component
- [ ] All vitest tests pass
- [ ] No production code changes are made
## Out of Scope
- TBD

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---
name: "Add test coverage for usePathCompletion hook"
---
# Story 113: Add test coverage for usePathCompletion hook
## User Story
As a developer, I want better test coverage for the usePathCompletion hook, so that regressions in path completion behavior are caught early.
## Acceptance Criteria
- [ ] usePathCompletion.ts reaches 95% coverage (currently 81.7%, 26 lines missing)
- [ ] Tests use renderHook to exercise all hook code paths
- [ ] All vitest tests pass
- [ ] No production code changes are made
## Out of Scope
- TBD

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---
name: "Web UI SSE socket stops updating after a while"
---
# Bug 114: Web UI SSE socket stops updating after a while
## Description
After the first several pipeline updates, the UI stops reflecting changes. Lozenges stop flying, stories stop moving between stages, but the server is still advancing the pipeline fine. A page refresh fixes it.
The root cause is likely not the SSE transport itself but rather the large combined pipeline state push that the frontend subscribes to. Investigate the SSE event handler in the frontend client — it receives a single big `pipeline_state` event that everything listens to. Something may be going wrong in the processing/diffing of that state after several rapid updates.
## Investigation hints
- Start with the SSE client in `frontend/src/api/client.ts` — look at `onPipelineState` handling
- Check if the SSE connection is actually dropping (add a log on close/error) or if events arrive but stop being processed
- The `LozengeFlyContext` diffing logic in `useLayoutEffect` compares prev vs current pipeline — could a stale ref or missed update break the chain?
- Server-side: the `broadcast::channel` has a 1024 buffer — if a slow consumer lags, tokio drops it silently
## How to Reproduce
1. Open the web UI
2. Start several agents working on stories
3. Wait a few minutes while agents complete and pipeline advances
4. Observe that the UI stops reflecting pipeline changes
5. Refresh the page — state is correct again
## Actual Result
UI freezes showing stale pipeline state after several updates.
## Expected Result
UI should always reflect current pipeline state in real time without needing a manual refresh.
## Acceptance Criteria
- [ ] Root cause identified (SSE transport vs frontend state processing)
- [ ] Fix implemented with auto-recovery if connection drops
- [ ] UI stays live through sustained agent activity (10+ minutes)

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---
name: "Hot-reload project.toml agent config without server restart"
---
# Story 115: Hot-reload project.toml agent config without server restart
## User Story
As a developer, I want changes to `.story_kit/project.toml` to be picked up automatically by the running server, so that I can update the agent roster without restarting the server.
## Acceptance Criteria
- [ ] When `.story_kit/project.toml` is saved on disk, the server detects the change within the debounce window (300 ms) and broadcasts an `agent_config_changed` WebSocket event to all connected clients
- [ ] The frontend `AgentPanel` automatically re-fetches and displays the updated agent roster upon receiving `agent_config_changed`, without any manual action
- [ ] `project.toml` changes inside worktree directories (paths containing `worktrees/`) are NOT broadcast
- [ ] Config file changes do NOT trigger a pipeline state refresh (only work-item events do)
- [ ] A helper `is_config_file(path, git_root)` correctly identifies the root-level `.story_kit/project.toml` (returns false for worktree copies)
## Out of Scope
- Watching for newly created `project.toml` (only file modification events)
- Validating the new config before broadcasting (parse errors are surfaced on next `get_agent_config` call)
- Reloading config into in-memory agent state (agents already read config from disk on each start)

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name: "Init command scaffolds deterministic project structure"
---
# Story 116: Init command scaffolds deterministic project structure
## User Story
As a new Story Kit user, I want to point at a directory and have the `.story_kit/` workflow structure scaffolded automatically, so that I have a working pipeline without manual configuration.
## Context
Currently `scaffold_story_kit()` in `server/src/io/fs.rs`:
- Creates the old `stories/archive/` structure instead of the `work/` pipeline dirs
- Writes `00_CONTEXT.md` and `STACK.md` with content that describes Story Kit itself, not a blank template for the user's project
- Does not create `project.toml` (agent config)
- Does not create `.mcp.json` (MCP endpoint registration)
- Does not run `git init`
- The embedded `STORY_KIT_README` constant is a stale copy that diverges from the actual `.story_kit/README.md` checked into this repo
## Acceptance Criteria
- [ ] Creates the `work/` pipeline: `work/1_upcoming/`, `work/2_current/`, `work/3_qa/`, `work/4_merge/`, `work/5_archived/` — each with a `.gitkeep` file so empty dirs survive git clone
- [ ] Removes creation of the old `stories/` and `stories/archive/` directories
- [ ] Creates `specs/`, `specs/tech/`, `specs/functional/` (unchanged)
- [ ] Creates `script/test` with the existing stub (unchanged)
- [ ] Writes `.story_kit/README.md` using `include_str!` to embed the canonical README.md at build time (replacing the stale `STORY_KIT_README` constant)
- [ ] Writes `.story_kit/project.toml` with a sensible default agent config (one coder agent, one qa agent, one mergemaster — using `sonnet` model aliases)
- [ ] Writes `.mcp.json` in the project root with the default port (reuse `write_mcp_json` from `worktree.rs`)
- [ ] Writes `specs/00_CONTEXT.md` as a blank template with section headings (High-Level Goal, Core Features, Domain Definition, Glossary) and placeholder instructions — NOT content about Story Kit itself
- [ ] Writes `specs/tech/STACK.md` as a blank template with section headings (Core Stack, Coding Standards, Quality Gates, Libraries) and placeholder instructions — NOT content about Story Kit itself
- [ ] Runs `git init` if the directory is not already a git repo
- [ ] Makes an initial commit with the scaffolded files (only on fresh `git init`, not into an existing repo)
- [ ] Unit tests for `scaffold_story_kit()` that run against a temp directory and verify: all expected directories exist, all expected files exist with correct content, `.gitkeep` files are present in work dirs, template specs contain placeholder headings (not Story Kit content), `project.toml` has valid default agent config, `.mcp.json` is valid JSON with correct endpoint
- [ ] Test that scaffold is idempotent — running it twice on the same directory doesn't overwrite or duplicate files
- [ ] Test that scaffold into an existing git repo does not run `git init` or create an initial commit
## Out of Scope
- Interactive onboarding (guided conversation to populate specs) — see Story 139
- Generating actual application code or project boilerplate (e.g. `cargo init`, `create-react-app`) — Story Kit is stack-agnostic, it only scaffolds the `.story_kit/` workflow layer
- Template galleries or presets for common stacks (future enhancement)
- Migrating existing projects that already have a `.story_kit/` directory

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name: "Show startup reconciliation progress in UI"
---
# Story 117: Show startup reconciliation progress in UI
## User Story
As a developer using Story Kit, I want to see what's happening during server startup reconciliation in the UI, so that I can understand why stories are moving between pipeline stages automatically.
## Acceptance Criteria
- [ ] The server emits `reconciliation_progress` WebSocket events during `reconcile_on_startup` with a `story_id`, `status`, and `message` for each story being processed
- [ ] The server emits a final `reconciliation_progress` event with `status: "done"` when reconciliation completes
- [ ] The frontend displays an in-progress indicator (e.g. a banner) while reconciliation is active, showing recent events
- [ ] The reconciliation banner dismisses itself when the `done` event is received
- [ ] Existing tests continue to pass
## Out of Scope
- Persisting reconciliation history across sessions
- Showing reconciliation progress for `auto_assign_available_work`

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name: "Agent pool retains stale running state after completion, blocking auto-assign"
---
# Bug 118: Agent pool retains stale running state after completion, blocking auto-assign
## Description
When an agent (QA, mergemaster) completes its work and the story advances in the pipeline, the agent pool still reports the agent as running on the old story. This blocks auto-assign from picking up new work in the queue.
This is different from bug 94 (stale state after restart). This happens during normal operation within a single server session.
## How to Reproduce
1. Have mergemaster complete a merge (e.g. story 106)
2. Story moves to archived
3. New items arrive in 4_merge/ (e.g. 107, 108, 109)
4. Try to start mergemaster on a new story
5. Server responds: Agent mergemaster is already running on story 106
## Actual Result
Agent pool reports mergemaster as running on the completed/archived story. Auto-assign skips the merge queue. Manual stop of the stale entry is required before the agent can be reassigned.
## Expected Result
When an agent process exits and the story advances, the agent pool should clear the running state so auto-assign can immediately dispatch the agent to the next queued item.
## Root Cause Analysis
The bug is in `server/src/agents.rs`, in the `start_agent` method.
### The Leak
In `start_agent` (line ~177), a `Pending` entry is inserted into the in-memory `HashMap<String, StoryAgent>` at line ~263:
```rust
{
let mut agents = self.agents.lock().map_err(|e| e.to_string())?;
agents.insert(
key.clone(),
StoryAgent {
agent_name: resolved_name.clone(),
status: AgentStatus::Pending,
// ...
},
);
}
```
Then at line ~290, `create_worktree` is called:
```rust
let wt_info = worktree::create_worktree(project_root, story_id, &config, self.port).await?;
```
**If `create_worktree` fails** (e.g. `pnpm run build` error during worktree setup), the function returns `Err` but **never removes the Pending entry** from the HashMap.
### The Blocking Effect
`find_free_agent_for_stage` (line ~1418) considers an agent "busy" if any HashMap entry has `Running | Pending` status:
```rust
let is_busy = agents.values().any(|a| {
a.agent_name == agent_config.name
&& matches!(a.status, AgentStatus::Running | AgentStatus::Pending)
});
```
The leaked Pending entry permanently blocks this agent from being auto-assigned until someone manually stops the stale entry via the API.
### Scope
This affects **all agent types** (coders, QA, mergemaster) equally — anywhere `start_agent` is called and the subsequent worktree creation or process spawn can fail. Anywhere there's a gate that can fail after the Pending entry is inserted, the leak can happen.
The code currently enforces gates but doesn't clean up if a gate fails — the Pending entry just stays in the HashMap forever.
### Fix Strategy
Add cleanup logic: if any step after the Pending insertion fails, remove the entry from the HashMap before returning the error. A guard/RAII pattern or explicit cleanup in the error path would both work. The key is that `start_agent` must be atomic — either the agent is fully started, or no trace of it remains in the pool.
Also audit other code paths that insert entries into the agents HashMap to ensure they all have proper cleanup on failure.
## Acceptance Criteria
- [ ] `start_agent` cleans up the Pending entry from the HashMap if `create_worktree` or any subsequent step fails
- [ ] No leaked Pending/Running entries remain after a failed agent start
- [ ] Automated test covers the failure case: simulate `create_worktree` failure and verify the agent pool is clean afterward
- [ ] All agent types (coder, QA, mergemaster) benefit from the fix
- [ ] Bug is fixed and verified with `cargo test` and `cargo clippy`

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---
name: "Mergemaster should resolve merge conflicts instead of leaving conflict markers on master"
---
# Story 119: Mergemaster should resolve merge conflicts instead of leaving conflict markers on master
## Problem
When mergemaster squash-merges a feature branch that conflicts with current master, conflict markers end up committed to master. This breaks the frontend build and requires manual intervention.
## Root Cause
There is a race condition between `run_squash_merge` and the file watcher:
1. `git merge --squash` runs on the main working tree
2. The squash brings `.story_kit/work/` files from the feature branch (e.g. story moved to `2_current`)
3. The watcher detects these file changes and auto-commits — including any conflict markers in frontend/server files
4. `run_squash_merge` checks the exit status and aborts, but the watcher already committed the broken state
The merge tool itself does the right thing (aborts on conflicts at `agents.rs:2157-2171`), but the watcher races it.
## Proposed Solution: Merge-Queue Branch
1. Create a `merge-queue` branch that always tracks master
2. Mergemaster performs squash-merges on `merge-queue` instead of master
3. If the merge is clean and gates pass, fast-forward master to merge-queue
4. If conflicts occur, the watcher does not care (it only watches the main worktree)
5. Mergemaster can resolve conflicts on the merge-queue branch without affecting master
6. If resolution fails, reset merge-queue to master and report the conflict
## Also Required: Pause Watcher During Merges
Add a lock/pause mechanism to the watcher that `merge_agent_work` acquires before running `git merge --squash`. The watcher skips auto-commits while the lock is held. This is a belt-and-suspenders defense — even with the merge-queue branch, we want the watcher to not interfere with merge operations.
**Implement both approaches** — the merge-queue branch for isolation, and the watcher pause as a safety net.
## Also Update Mergemaster Prompt
- Remove the instruction to NOT resolve conflicts
- Instead instruct mergemaster to resolve simple conflicts (e.g. both branches adding code at same location)
- For complex conflicts (semantic changes to the same logic), still report to human
## Key Files
- `server/src/agents.rs` — `run_squash_merge` (lines 2136-2199), `merge_agent_work` (lines 992-1066)
- `server/src/http/mcp.rs` — `tool_merge_agent_work` (lines 1392-1425)
- `server/src/io/watcher.rs` — file watcher that races with the merge
- `.story_kit/project.toml` — mergemaster prompt (lines 210-232)
## Acceptance Criteria
- [ ] Merge conflicts never leave conflict markers on master
- [ ] Mergemaster resolves simple additive conflicts automatically
- [ ] Complex conflicts are reported clearly without breaking master
- [ ] Frontend build stays clean throughout the merge process
- [ ] Existing tests pass

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---
name: Left-Align Chat Text and Add Syntax Highlighting
---
# Story: Left-Align Chat Text and Add Syntax Highlighting
## User Story
**As a** User
**I want** chat messages and code to be left-aligned instead of centered, with proper syntax highlighting for code blocks
**So that** the text is more readable, follows standard chat UI conventions, and code is easier to understand.
## Acceptance Criteria
* [x] User messages should be right-aligned (standard chat pattern)
* [x] Assistant messages should be left-aligned
* [x] Tool outputs should be left-aligned
* [x] Code blocks and monospace text should be left-aligned
* [x] Remove any center-alignment styling from the chat container
* [x] Maintain the current max-width constraint for readability
* [x] Ensure proper spacing and padding for visual hierarchy
* [x] Add syntax highlighting for code blocks in assistant messages
* [x] Support common languages: JavaScript, TypeScript, Rust, Python, JSON, Markdown, Shell, etc.
* [x] Syntax highlighting should work with the dark theme
## Out of Scope
* Redesigning the entire chat layout
* Adding avatars or profile pictures
* Changing the overall color scheme or theme (syntax highlighting colors should complement existing dark theme)
* Custom themes for syntax highlighting
## Implementation Notes
* Check `Chat.tsx` for any `textAlign: "center"` styles
* Check `App.css` for any center-alignment rules affecting the chat
* User messages should align to the right with appropriate styling
* Assistant and tool messages should align to the left
* Code blocks should always be left-aligned for readability
* For syntax highlighting, consider using:
* `react-syntax-highlighter` (works with react-markdown)
* Or `prism-react-renderer` for lighter bundle size
* Or integrate with `rehype-highlight` plugin for react-markdown
* Use a dark theme preset like `oneDark`, `vsDark`, or `dracula`
* Syntax highlighting should be applied to markdown code blocks automatically
## Related Functional Specs
* Functional Spec: UI/UX

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name: "Add test coverage for llm/chat.rs (2.6% -> 60%+)"
---
# Story 120: Add test coverage for llm/chat.rs
Currently at 2.6% line coverage (343 lines, 334 missed). This is the chat completion orchestration layer — the biggest uncovered module by missed line count.
## What to test
- Message construction and formatting
- Token counting/estimation logic
- Chat session management
- Error handling paths (provider errors, timeout, malformed responses)
- Any pure functions that don't require a live LLM connection
## Notes
- Mock the LLM provider trait/interface rather than making real API calls
- Focus on the logic layer, not the provider integration
- Target 60%+ line coverage
## Acceptance Criteria
- [ ] Line coverage for `llm/chat.rs` reaches 60%+
- [ ] Tests pass with `cargo test`
- [ ] `cargo clippy` clean

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name: "Add test coverage for io/watcher.rs (40% -> 70%+)"
---
# Story 121: Add test coverage for io/watcher.rs
Currently at 40% line coverage (238 lines, 142 missed). The file watcher is critical infrastructure — it drives pipeline advancement and auto-commits.
## What to test
- Story file detection and classification (which directory, what kind of move)
- Debounce/flush logic
- Git add/commit message generation
- Watcher pause/resume mechanism (added in story 119 for merge safety)
- Edge cases: rapid file changes, missing directories, git failures
## Notes
- Use temp directories for filesystem tests
- Mock git commands where needed
- The watcher pause lock is especially important to test given its role in merge safety
## Acceptance Criteria
- [ ] Line coverage for `io/watcher.rs` reaches 70%+
- [ ] Tests pass with `cargo test`
- [ ] `cargo clippy` clean

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name: "Add test coverage for http/ws.rs (0% -> 50%+)"
---
# Story 122: Add test coverage for http/ws.rs
Currently at 0% line coverage (160 lines). This is the WebSocket handler that powers the real-time UI — pipeline state pushes, chat streaming, permission requests, and reconciliation progress.
## What to test
- WebSocket message parsing (incoming WsRequest variants)
- Pipeline state serialization to WsResponse
- Message routing (chat, cancel, permission_response)
- Connection lifecycle (open, close, reconnect handling server-side)
- Broadcast channel subscription and message delivery
## Notes
- May need to set up a test server context or mock the broadcast channel
- Focus on the message handling logic rather than actual WebSocket transport
- Test the serialization/deserialization of all WsResponse variants
## Acceptance Criteria
- [ ] Line coverage for `http/ws.rs` reaches 50%+
- [ ] Tests pass with `cargo test`
- [ ] `cargo clippy` clean

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name: "Add test coverage for llm/providers/anthropic.rs (0% -> 50%+)"
---
# Story 123: Add test coverage for llm/providers/anthropic.rs
Currently at 0% line coverage (204 lines). The Anthropic provider handles API communication for Claude models.
## What to test
- Request construction (headers, body format, model selection)
- Response parsing (streaming chunks, tool use responses, error responses)
- API key validation
- Rate limit / error handling
- Message format conversion (internal Message -> Anthropic API format)
## Notes
- Mock HTTP responses rather than calling the real Anthropic API
- Use `mockito` or similar for HTTP mocking, or test the pure functions directly
- Focus on serialization/deserialization and error paths
## Acceptance Criteria
- [ ] Line coverage for `llm/providers/anthropic.rs` reaches 50%+
- [ ] Tests pass with `cargo test`
- [ ] `cargo clippy` clean

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name: "Add test coverage for llm/providers/claude_code.rs (54% -> 75%+)"
---
# Story 124: Add test coverage for llm/providers/claude_code.rs
Currently at 54% line coverage (496 lines, 259 missed). The Claude Code provider spawns `claude` CLI processes and manages their I/O.
## What to test
- Command argument construction (model, max-turns, budget, system prompt, append flags)
- Output parsing (streaming JSON events from claude CLI)
- Session ID extraction
- Process lifecycle management
- Error handling (process crash, invalid output, timeout)
- Permission request/response flow
## Notes
- Mock the process spawning rather than running real `claude` commands
- Test the output parsing logic with sample JSON event streams
- The argument construction logic is especially testable as pure functions
## Acceptance Criteria
- [ ] Line coverage for `llm/providers/claude_code.rs` reaches 75%+
- [ ] Tests pass with `cargo test`
- [ ] `cargo clippy` clean

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name: "Add test coverage for http/io.rs (0% -> 60%+)"
---
# Story 125: Add test coverage for http/io.rs
Currently at 0% line coverage (76 lines). These are the IO-related HTTP endpoints (absolute path listing, directory creation, home directory).
## What to test
- `list_directory_absolute` endpoint — valid path, invalid path, permission errors
- `create_directory_absolute` endpoint — new dir, existing dir, nested creation
- `get_home_directory` endpoint — returns correct home path
- Error responses for invalid inputs
## Notes
- Use temp directories for filesystem tests
- These are straightforward CRUD-style endpoints, should be quick to cover
- Follow the test patterns used in `http/project.rs` and `http/settings.rs`
## Acceptance Criteria
- [ ] Line coverage for `http/io.rs` reaches 60%+
- [ ] Tests pass with `cargo test`
- [ ] `cargo clippy` clean

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name: "Add test coverage for http/anthropic.rs (0% -> 60%+)"
---
# Story 126: Add test coverage for http/anthropic.rs
Currently at 0% line coverage (66 lines). These are the Anthropic-related HTTP endpoints (key exists check, models list, set API key).
## What to test
- `get_anthropic_api_key_exists` — returns true/false based on stored key
- `get_anthropic_models` — returns model list
- `set_anthropic_api_key` — stores key, validates format
- Error handling for missing/invalid keys
## Notes
- Follow the test patterns in `http/settings.rs` and `http/model.rs`
- Small file, should be quick to get good coverage
- Mock any external API calls
## Acceptance Criteria
- [ ] Line coverage for `http/anthropic.rs` reaches 60%+
- [ ] Tests pass with `cargo test`
- [ ] `cargo clippy` clean

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name: "Add test coverage for http/mod.rs (39% -> 70%+)"
---
# Story 127: Add test coverage for http/mod.rs
Currently at 39% line coverage (77 lines, 47 missed). This is the HTTP route setup and server initialization module.
## What to test
- Route registration (all expected paths are mounted)
- CORS configuration
- Static asset serving setup
- Server builder configuration
- Any middleware setup
## Notes
- May need integration-style tests that start a test server and verify routes exist
- Or test the route builder functions in isolation
- Follow patterns from existing HTTP module tests
## Acceptance Criteria
- [ ] Line coverage for `http/mod.rs` reaches 70%+
- [ ] Tests pass with `cargo test`
- [ ] `cargo clippy` clean

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name: "Add test coverage for worktree.rs (65% -> 80%+)"
---
# Story 128: Add test coverage for worktree.rs
Currently at 65% line coverage (330 lines, 124 missed). Worktree management is core infrastructure — creating, removing, and managing git worktrees for agent isolation.
## What to test
- `worktree_path` construction
- `create_worktree` — branch naming, git worktree add, setup command execution
- `remove_worktree_by_story_id` — cleanup, branch deletion
- Setup command runner (pnpm install, pnpm build, cargo check)
- Error paths: git failures, setup failures, missing directories
- Edge cases: worktree already exists, branch already exists
## Notes
- Use temp git repos for integration tests
- Mock expensive operations (pnpm install, cargo check) where possible
- The setup command failure path is especially important (this was the root cause of bug 118)
## Acceptance Criteria
- [ ] Line coverage for `worktree.rs` reaches 80%+
- [ ] Tests pass with `cargo test`
- [ ] `cargo clippy` clean

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name: "Add test coverage for http/mcp.rs (72% -> 85%+)"
---
# Story 129: Add test coverage for http/mcp.rs
Currently at 72% line coverage (1826 lines, 475 missed). This is the MCP tool server — the largest module and the interface agents use to interact with the system.
## What to test
- Uncovered MCP tool handlers (check which tools lack test coverage)
- Tool argument validation and error messages
- Edge cases in existing tool handlers
- The merge-queue and watcher-pause logic (added in story 119)
- `resolve_simple_conflicts` edge cases
- Tool dispatch routing
## Notes
- This is a large file — focus on the uncovered handlers rather than trying to test everything
- Run `cargo llvm-cov --html` to identify specific uncovered lines/functions
- The merge-related tools are the most critical gaps given recent changes
- 475 missed lines is a lot — even covering half would be a big win
## Acceptance Criteria
- [ ] Line coverage for `http/mcp.rs` reaches 85%+
- [ ] Tests pass with `cargo test`
- [ ] `cargo clippy` clean

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---
name: Be Able to Use Claude
---
# Story 12: Be Able to Use Claude
## User Story
As a user, I want to be able to select Claude (via Anthropic API) as my LLM provider so I can use Claude models instead of only local Ollama models.
## Acceptance Criteria
- [x] Claude models appear in the unified model dropdown (same dropdown as Ollama models)
- [x] Dropdown is organized with section headers: "Anthropic" and "Ollama" with models listed under each
- [x] When user first selects a Claude model, a dialog prompts for Anthropic API key
- [x] API key is stored securely (using Tauri store plugin for reliable cross-platform storage)
- [x] Provider is auto-detected from model name (starts with `claude-` = Anthropic, otherwise = Ollama)
- [x] Chat requests route to Anthropic API when Claude model is selected
- [x] Streaming responses work with Claude (token-by-token display)
- [x] Tool calling works with Claude (using Anthropic's tool format)
- [x] Context window calculation accounts for Claude models (200k tokens)
- [x] User's model selection persists between sessions
- [x] Clear error messages if API key is missing or invalid
## Out of Scope
- Support for other providers (OpenAI, Google, etc.) - can be added later
- API key management UI (rotation, multiple keys, view/edit key after initial entry)
- Cost tracking or usage monitoring
- Model fine-tuning or custom models
- Switching models mid-conversation (user can start new session)
- Fetching available Claude models from API (hardcoded list is fine)
## Technical Notes
- Anthropic API endpoint: `https://api.anthropic.com/v1/messages`
- API key should be stored securely (environment variable or secure storage)
- Claude models support tool use (function calling)
- Context windows: claude-3-5-sonnet (200k), claude-3-5-haiku (200k)
- Streaming uses Server-Sent Events (SSE)
- Tool format differs from OpenAI/Ollama - needs conversion
## Design Considerations
- Single unified model dropdown with section headers ("Anthropic", "Ollama")
- Use `<optgroup>` in HTML select for visual grouping
- API key dialog appears on-demand (first use of Claude model)
- Store API key in OS keychain using `keyring` crate (cross-platform)
- Backend auto-detects provider from model name pattern
- Handle API key in backend only (don't expose to frontend logs)
- Alphabetical sorting within each provider section
## Implementation Approach
### Backend (Rust)
1. Add `anthropic` feature/module for Claude API client
2. Create `AnthropicClient` with streaming support
3. Convert tool definitions to Anthropic format
4. Handle Anthropic streaming response format
5. Add API key storage (encrypted or environment variable)
### Frontend (TypeScript)
1. Add hardcoded list of Claude models (claude-3-5-sonnet-20241022, claude-3-5-haiku-20241022)
2. Merge Ollama and Claude models into single dropdown with `<optgroup>` sections
3. Create API key input dialog/modal component
4. Trigger API key dialog when Claude model selected and no key stored
5. Add Tauri command to check if API key exists in keychain
6. Add Tauri command to set API key in keychain
7. Update context window calculations for Claude models (200k tokens)
### API Differences
- Anthropic uses `messages` array format (similar to OpenAI)
- Tools are called `tools` with different schema
- Streaming events have different structure
- Need to map our tool format to Anthropic's format
## Security Considerations
- API key stored in OS keychain (not in files or environment variables)
- Use `keyring` crate for cross-platform secure storage
- Never log API key in console or files
- Backend validates API key format before making requests
- Handle API errors gracefully (rate limits, invalid key, network errors)
- API key only accessible to the app process
## UI Flow
1. User opens model dropdown → sees "Anthropic" section with Claude models, "Ollama" section with local models
2. User selects `claude-3-5-sonnet-20241022`
3. Backend checks Tauri store for saved API key
4. If not found → Frontend shows dialog: "Enter your Anthropic API key"
5. User enters key → Backend stores in Tauri store (persistent JSON file)
6. Chat proceeds with Anthropic API
7. Future sessions: API key auto-loaded from store (no prompt)
## Implementation Notes (Completed)
### Storage Solution
Initially attempted to use the `keyring` crate for OS keychain integration, but encountered issues in macOS development mode:
- Unsigned Tauri apps in dev mode cannot reliably access the system keychain
- The `keyring` crate reported successful saves but keys were not persisting
- No macOS keychain permission dialogs appeared
**Solution:** Switched to Tauri's `store` plugin (`tauri-plugin-store`)
- Provides reliable cross-platform persistent storage
- Stores data in a JSON file managed by Tauri
- Works consistently in both development and production builds
- Simpler implementation without platform-specific entitlements
### Key Files Modified
- `src-tauri/src/commands/chat.rs`: API key storage/retrieval using Tauri store
- `src/components/Chat.tsx`: API key dialog and flow with pending message preservation
- `src-tauri/Cargo.toml`: Removed `keyring` dependency, kept `tauri-plugin-store`
- `src-tauri/src/llm/anthropic.rs`: Anthropic API client with streaming support
### Frontend Implementation
- Added `pendingMessageRef` to preserve user's message when API key dialog is shown
- Modified `sendMessage()` to accept optional message parameter for retry scenarios
- API key dialog appears on first Claude model usage
- After saving key, automatically retries sending the pending message
### Backend Implementation
- `get_anthropic_api_key_exists()`: Checks if API key exists in store
- `set_anthropic_api_key()`: Saves API key to store with verification
- `get_anthropic_api_key()`: Retrieves API key for Anthropic API calls
- Provider auto-detection based on `claude-` model name prefix
- Tool format conversion from internal format to Anthropic's schema
- SSE streaming implementation for real-time token display

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name: "Permission approval returns wrong format — tools fail after user approves"
---
# Bug 130: Permission approval returns wrong format — tools fail after user approves
## Description
The `prompt_permission` MCP tool returns plain text ("Permission granted for '...'") but Claude Code's `--permission-prompt-tool` expects a JSON object with a `behavior` field. After the user approves a permission request in the web UI dialog, every tool call fails with a Zod validation error: `"expected object, received null"`.
## How to Reproduce
1. Start the story-kit server and open the web UI
2. Chat with the claude-code-pty model
3. Ask it to do something that requires a tool NOT in `.claude/settings.json` allow list (e.g. `wc -l /etc/hosts`, or WebFetch to a non-allowed domain)
4. The permission dialog appears — click Approve
5. Observe the tool call fails with: `[{"code":"invalid_union","errors":[[{"expected":"object","code":"invalid_type","path":[],"message":"Invalid input: expected object, received null"}]],"path":[],"message":"Invalid input"}]`
## Actual Result
After approval, the tool fails with a Zod validation error. Claude Code cannot parse the plain-text response as a permission decision.
## Expected Result
After approval, the tool executes successfully. The MCP tool should return JSON that Claude Code understands: `{"behavior": "allow"}` for approval or `{"behavior": "deny", "message": "..."}` for denial.
## Acceptance Criteria
- [ ] prompt_permission returns `{"behavior": "allow"}` JSON when user approves
- [ ] prompt_permission returns `{"behavior": "deny"}` JSON when user denies
- [ ] After approving a permission request, the tool executes successfully and returns its result
- [ ] After denying a permission request, the tool is skipped gracefully

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name: "get_agent_output stream always times out for running agents"
---
# Bug 131: get_agent_output stream always times out for running agents
## Description
The `get_agent_output` MCP tool consistently returns "Stream timed out; call again to continue" even when the agent process is actively running, making API calls, and committing work. The `list_agents` call shows the agent as `running` with `session_id: null` throughout its entire execution, only populating the session_id after the process exits. This makes it impossible to observe agent progress in real time via MCP.
## How to Reproduce
1. Start an agent on a story (e.g. `start_agent` with `coder-1`)
2. Confirm the claude process is running (`ps aux | grep claude`)
3. Call `get_agent_output` with the story_id and agent_name
4. Observe it returns "Stream timed out" every time, regardless of timeout_ms value (tested up to 10000ms)
5. `list_agents` shows `session_id: null` throughout
6. Agent completes its work and commits without ever producing observable output
## Actual Result
`get_agent_output` never returns any events. `session_id` stays null while the agent is running. The only way to observe progress is to poll the worktree's git log directly.
## Expected Result
`get_agent_output` streams back text tokens and status events from the running agent in real time. `session_id` is populated once the agent's first streaming event arrives.
## Reopened — Previous Fix Did Not Work
This was archived after a coder pass but the bug is still present. With 3 agents actively running:
- `get_agent_output` returned 141 events on one call, then 0 events on the next call with a 5s timeout
- None of the events contained text output — only metadata/status events
- The server logs (`get_server_logs`) DO show agent activity (spawn commands, MCP calls), so the agents are working — the output just isn't being captured/forwarded
### Investigation needed
The coder needs to trace the full data path:
1. How does `run_agent_pty_streaming` (server/src/agents.rs) capture PTY output from the claude process?
2. How are those events published to the broadcast channel that `get_agent_output` subscribes to?
3. Is the broadcast channel being created before the agent starts producing output, or is there a race where early events are lost?
4. Are text tokens from the PTY being sent as `AgentEvent` variants that `get_agent_output` actually serializes, or are they filtered out?
## Acceptance Criteria
- [ ] get_agent_output returns streaming text events while an agent is actively running
- [ ] session_id is populated in list_agents shortly after agent spawn
- [ ] Calling get_agent_output multiple times yields incremental output from the agent

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name: "Fix TOCTOU race in agent check-and-insert"
---
# Story 132: Fix TOCTOU race in agent check-and-insert
## User Story
As a user running multiple agents, I want the agent pool to correctly enforce single-instance-per-agent so that two agents never end up running on the same story or the same agent name running on two stories concurrently.
## Acceptance Criteria
- [ ] The lock in start_agent (server/src/agents.rs ~lines 262-324) is held continuously from the availability check through the HashMap insert — no lock release between check and insert
- [ ] The lock in auto_assign_available_work (server/src/agents.rs ~lines 1196-1228) is held from find_free_agent_for_stage through the start_agent call, preventing a concurrent auto_assign from selecting the same agent
- [ ] A test demonstrates that concurrent start_agent calls for the same agent name on different stories result in exactly one running agent and one rejection
- [ ] A test demonstrates that concurrent auto_assign_available_work calls do not produce duplicate assignments
## Analysis
### Race 1: start_agent check-then-insert (server/src/agents.rs)
The single-instance check at ~lines 262-296 acquires the mutex, checks for duplicate agents, then **releases the lock**. The HashMap insert happens later at ~line 324 after **re-acquiring the lock**. Between release and reacquire, a concurrent call can pass the same check:
```
Thread A: lock → check coder-1 available? YES → unlock
Thread B: lock → check coder-1 available? YES → unlock → lock → insert "86:coder-1"
Thread A: lock → insert "130:coder-1"
Result: both coder-1 entries exist, two processes spawned
```
The composite key at ~line 27 is `format!("{story_id}:{agent_name}")`, so `86:coder-1` and `130:coder-1` are different keys. The name-only check at ~lines 277-295 iterates the HashMap looking for a Running/Pending agent with the same name — but both threads read the HashMap before either has inserted, so both pass.
**Fix**: Hold the lock from the check (~line 264) through the insert (~line 324). This means the worktree setup and process spawn (~lines 297-322) must either happen inside the lock (blocking other callers) or the entry must be inserted as `Pending` before releasing the lock, with the process spawn happening after.
### Race 2: auto_assign_available_work (server/src/agents.rs)
At ~lines 1196-1215, the function locks the mutex, calls `find_free_agent_for_stage` to pick an available agent name, then **releases the lock**. It then calls `start_agent` at ~line 1228, which re-acquires the lock. Two concurrent `auto_assign` calls can both select the same free agent for different stories (or the same story) in this window.
**Fix**: Either hold the lock across the full loop iteration, or restructure so that `start_agent` receives a reservation/guard rather than just an agent name string.
### Observed symptoms
- Both `coder-1` and `coder-2` showing as "running" on the same story
- `coder-1` appearing on story 86 immediately after completing on bug 130, due to pipeline advancement calling `auto_assign_available_work` concurrently with other state transitions
## Out of Scope
- TBD

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name: "Clean up agent state on story archive and add TTL for completed entries"
---
# Story 133: Clean up agent state on story archive and add TTL for completed entries
## User Story
As a user, I want completed and archived agent entries to be cleaned up automatically so that the agent pool reflects reality and stale entries do not accumulate or confuse the UI.
## Acceptance Criteria
- [ ] When a story is archived (move_story_to_archived), all agent entries for that story_id are removed from the HashMap
- [ ] Completed and Failed agent entries are automatically removed after a configurable TTL (default 1 hour)
- [ ] list_agents never returns agents for archived stories, even without the filesystem filter fallback
- [ ] A test demonstrates that archiving a story removes its agent entries from the pool
- [ ] A test demonstrates that completed entries are reaped after TTL expiry
## Out of Scope
- TBD

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name: "Add process health monitoring and timeout to agent PTY sessions"
---
# Story 134: Add process health monitoring and timeout to agent PTY sessions
## User Story
As a user, I want hung or unresponsive agent processes to be detected and cleaned up automatically so that the system recovers without manual intervention.
## Acceptance Criteria
- [ ] The PTY read loop has a configurable inactivity timeout (default 5 minutes) — if no output is received within the timeout, the process is killed and the agent status set to Failed
- [ ] A background watchdog task periodically checks that Running agents still have a live process, and marks orphaned entries as Failed
- [ ] When an agent process is killed externally (e.g. SIGKILL), the agent status transitions to Failed within the timeout period rather than hanging indefinitely
- [ ] A test demonstrates that a hung agent (no PTY output) is killed and marked Failed after the timeout
- [ ] A test demonstrates that an externally killed agent is detected and cleaned up by the watchdog
## Out of Scope
- TBD

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name: "Update mergemaster prompt to allow conflict resolution and code fixes"
---
# Story 135: Update mergemaster prompt to allow conflict resolution and code fixes
## User Story
As a user, I want the mergemaster agent to be able to resolve simple conflicts and fix minor gate failures itself, instead of being told to never write code and looping infinitely on failures.
## Acceptance Criteria
- [ ] The mergemaster prompt in project.toml no longer says "Do NOT implement code yourself" or "Do not write code"
- [ ] The mergemaster prompt instructs the agent to resolve simple additive conflicts (both branches adding code at the same location) automatically
- [ ] The mergemaster prompt instructs the agent to attempt minor fixes when quality gates fail (e.g. syntax errors, missing semicolons) rather than just reporting and looping
- [ ] For complex conflicts or non-trivial gate failures, the mergemaster prompt instructs the agent to report clearly to the human rather than attempting a fix
- [ ] The system_prompt field is updated to match the new prompt behaviour
- [ ] The mergemaster prompt includes a max retry limit instruction — if gates fail after 2 fix attempts, stop and report to the human instead of retrying
## Out of Scope
- TBD

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name: "Broadcast channel silently drops events on subscriber lag"
---
# Bug 136: Broadcast channel silently drops events on subscriber lag
## Description
The watcher broadcast channel (capacity 1024) silently drops events when a subscriber lags behind. In the WebSocket handler, the `Lagged` error is caught and handled with a bare `continue`, meaning the frontend never receives those state updates and falls out of sync.
## How to Reproduce
1. Open the web UI
2. Start agents that generate pipeline state changes
3. If the WebSocket consumer is momentarily slow (e.g., blocked on send), the broadcast subscriber falls behind
4. Lagged events are silently skipped
## Actual Result
Events are silently dropped with `continue` on `RecvError::Lagged`. The frontend misses state transitions and shows stale data.
## Expected Result
When a lag occurs, the system should recover by re-sending the full current pipeline state so the frontend catches up, rather than silently dropping events.
## Acceptance Criteria
- [ ] Lagged broadcast events trigger a full state resync to the affected subscriber
- [ ] No silent event drops — lag events are logged as warnings

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name: "LozengeFlyContext animation queue race condition on rapid updates"
---
# Bug 137: LozengeFlyContext animation queue race condition on rapid updates
## Description
In LozengeFlyContext.tsx, the useEffect that executes animations clears pending action refs at the start of each run. When rapid pipeline updates arrive, useLayoutEffect queues actions into refs, but the useEffect can clear them before they're processed. This breaks the diffing chain and causes the UI to stop reflecting state changes.
## How to Reproduce
1. Open the web UI
2. Trigger several pipeline state changes in quick succession (e.g., start multiple agents)
3. Observe that lozenge animations stop firing after a few updates
4. The pipeline state in the server is correct but the UI is stale
## Actual Result
The useEffect clears pendingFlyInActionsRef before processing, racing with useLayoutEffect that queues new actions. After a few rapid updates the animation queue gets into an inconsistent state and stops processing.
## Expected Result
Animation queue should handle rapid pipeline updates without losing actions or breaking the diffing chain.
## Acceptance Criteria
- [ ] No animation actions are lost during rapid pipeline updates
- [ ] Lozenge fly animations remain functional through sustained agent activity

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name: "No heartbeat to detect stale WebSocket connections"
---
# Bug 138: No heartbeat to detect stale WebSocket connections
## Description
The WebSocket client in frontend/src/api/client.ts only reconnects when the onclose event fires. If the connection half-closes (appears open but stops receiving data), onclose never fires and reconnection never happens. There is no ping/pong heartbeat mechanism to detect this state.
## How to Reproduce
1. Open the web UI and establish a WebSocket connection
2. Wait for a network disruption or half-close scenario
3. The connection appears open but stops delivering messages
4. No reconnection is attempted
## Actual Result
The frontend keeps a dead WebSocket open indefinitely with no way to detect it has stopped receiving data. UI becomes permanently stale until manual refresh.
## Expected Result
A heartbeat mechanism should detect stale connections and trigger automatic reconnection.
## Acceptance Criteria
- [ ] WebSocket client implements a periodic heartbeat/ping to detect stale connections
- [ ] Stale connections are automatically closed and reconnected
- [ ] Server responds to ping frames or implements server-side keepalive

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name: "Retry limit for mergemaster and pipeline restarts"
---
# Story 139: Retry limit for mergemaster and pipeline restarts
## User Story
As a developer using story-kit, I want pipeline auto-restarts to have a configurable retry limit so that failing agents don't loop infinitely consuming CPU and API credits.
## Acceptance Criteria
- [ ] Pipeline auto-restart has a configurable max_retries per agent in project.toml (default 3)
- [ ] After max retries exhausted, agent status is set to Failed and no further restarts occur
- [ ] Server logs clearly indicate attempt number and when max retries are exhausted
- [ ] Retry count resets when a human manually restarts the agent (resume_context is None)
- [ ] Retry limit applies to all pipeline stages: Coder, QA, and Mergemaster restarts
## Out of Scope
- TBD

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name: Stop Button
---
# Story 13: Stop Button
## User Story
**As a** User
**I want** a Stop button to cancel the model's response while it's generating
**So that** I can immediately stop long-running or unwanted responses without waiting for completion
## The Problem
**Current Behavior:**
- User sends message → Model starts generating
- User realizes they don't want the response (wrong question, too long, etc.)
- **No way to stop it** - must wait for completion
- Tool calls will execute even if user wants to cancel
**Why This Matters:**
- Long responses waste time
- Tool calls have side effects (file writes, searches, shell commands)
- User has no control once generation starts
- Standard UX pattern in ChatGPT, Claude, etc.
## Acceptance Criteria
- [ ] Stop button (⬛) appears in place of Send button (↑) while model is generating
- [ ] Clicking Stop immediately cancels the backend request
- [ ] Tool calls that haven't started yet are NOT executed after cancellation
- [ ] Streaming stops immediately
- [ ] Partial response generated before stopping remains visible in chat
- [ ] Stop button becomes Send button again after cancellation
- [ ] User can immediately send a new message after stopping
- [ ] Input field remains enabled during generation
## Out of Scope
- Escape key shortcut (can add later)
- Confirmation dialog (immediate action is better UX)
- Undo/redo functionality
- New Session flow (that's Story 14)
## Implementation Approach
### Backend
- Add `cancel_chat` command callable from frontend
- Use `tokio::select!` to race chat execution vs cancellation signal
- Check cancellation before executing each tool
- Return early when cancelled (not an error - expected behavior)
### Frontend
- Replace Send button with Stop button when `loading` is true
- On Stop click: call `invoke("cancel_chat")` and set `loading = false`
- Keep input enabled during generation
- Visual: Make Stop button clearly distinct (⬛ or "Stop" text)
## Testing Strategy
1. **Test Stop During Streaming:**
- Send message requesting long response
- Click Stop while streaming
- Verify streaming stops immediately
- Verify partial response remains visible
- Verify can send new message
2. **Test Stop Before Tool Execution:**
- Send message that will use tools
- Click Stop while "thinking" (before tool executes)
- Verify tool does NOT execute (check logs/filesystem)
3. **Test Stop During Tool Execution:**
- Send message with multiple tool calls
- Click Stop after first tool executes
- Verify remaining tools do NOT execute
## Success Criteria
**Before:**
- User sends message → No way to stop → Must wait for completion → Frustrating UX
**After:**
- User sends message → Stop button appears → User clicks Stop → Generation cancels immediately → Partial response stays → Can send new message
## Related Stories
- Story 14: New Session Cancellation (same backend mechanism, different trigger)
- Story 18: Streaming Responses (Stop must work with streaming)

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name: "Activity status indicator never visible due to display condition"
---
# Bug 140: Activity status indicator never visible due to display condition
## Description
Story 86 wired up live activity status end-to-end (server emits tool_activity events over WebSocket, frontend receives them and calls setActivityStatus), but the UI condition `loading && !streamingContent` on line 686 of Chat.tsx guarantees the activity labels are never visible.
The timeline within a Claude Code turn:
1. Model starts generating text → onToken fires → streamingContent accumulates → streaming bubble shown, activity indicator hidden
2. Model decides to call a tool → content_block_start with tool_use arrives → setActivityStatus("Reading file...") fires
3. But streamingContent is still full of text from step 1 → condition !streamingContent is false → activity never renders
4. onUpdate arrives with the complete assistant message → setStreamingContent("") → now !streamingContent is true, but the next turn starts immediately or loading ends
The "Thinking..." fallback only shows in the brief window before the very first token of a request arrives — and at that point no tool has been called yet, so activityStatus is still null.
## How to Reproduce
1. Open the Story Kit web UI chat
2. Send any message that causes the agent to use tools (e.g. ask it to read a file)
3. Watch the thinking indicator
## Actual Result
The indicator always shows "Thinking..." and never changes to activity labels like "Reading file...", "Writing file...", etc.
## Expected Result
The indicator should cycle through tool activity labels (e.g. "Reading file...", "Executing command...") as the agent works, as specified in Story 86's acceptance criteria.
## Acceptance Criteria
- [ ] Activity status labels (e.g. 'Reading file...', 'Executing command...') are visible in the UI when the agent calls tools
- [ ] Activity is shown even when streamingContent is non-empty (e.g. between assistant turns or alongside the streaming bubble)
- [ ] The indicator still falls back to 'Thinking...' when no tool activity is in progress

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name: "Improve server logging with timestamps and error visibility"
---
# Story 141: Improve server logging with timestamps and error visibility
## User Story
As a developer operating the system, I want server logs to include timestamps and surface errors and warnings prominently, so that I can diagnose problems instead of guessing why things silently failed.
## Acceptance Criteria
- [ ] All log lines emitted by slog!() include an ISO 8601 timestamp prefix
- [ ] Errors and warnings are logged at distinct severity levels (e.g. ERROR, WARN, INFO) so they can be filtered and stand out visually
- [ ] Agent lifecycle failures (process crashes, gate failures, worktree setup failures, pipeline advancement errors) are logged at ERROR or WARN level rather than silently swallowed
- [ ] MCP tool call failures are logged at WARN level with the tool name and error details
- [ ] Permission request timeouts and denials are logged at WARN level
- [ ] The get_server_logs MCP tool supports filtering by severity level (e.g. filter by ERROR to see only errors)
## Out of Scope
- TBD

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name: "Quality gates run after fast-forward to master instead of before"
---
# Bug 142: Quality gates run after fast-forward to master instead of before
## Description
## Bug
The `merge_agent_work` function in `server/src/agents.rs` runs quality gates AFTER the squash merge has already been fast-forwarded to master. This means broken code lands on master before gates catch it.
### Current Flow (broken)
1. `run_squash_merge()` creates merge-queue branch + temp worktree
2. Squash merge + conflict resolution in temp worktree
3. **Fast-forward master to merge-queue commit** (line 2522)
4. Clean up temp worktree + branch
5. `run_merge_quality_gates()` runs on master (line 1047)
6. If gates fail, broken code is already on master
### Expected Flow
1. `run_squash_merge()` creates merge-queue branch + temp worktree
2. Squash merge + conflict resolution in temp worktree
3. **Run quality gates in the merge-queue worktree BEFORE fast-forward**
4. If gates fail: report failure back to mergemaster with the temp worktree still intact, so mergemaster can attempt fixes there (up to 2 attempts per story 135's prompt)
5. If gates still fail after mergemaster's retry attempts: tear down temp worktree + branch, leave master untouched, report to human
6. If gates pass: fast-forward master, clean up
### Key Files
- `server/src/agents.rs` line 1013: `merge_agent_work()` — orchestrator
- `server/src/agents.rs` line 2367: `run_squash_merge()` — does merge + fast-forward
- `server/src/agents.rs` line 2522: fast-forward step that should happen AFTER gates
- `server/src/agents.rs` line 1047: `run_merge_quality_gates()` — runs too late
### Impact
Broken merges (conflict markers, missing braces) land on master and break all worktrees that pull from it. Mergemaster then has to fix master directly, adding noise commits.
## How to Reproduce
1. Have a feature branch with code that conflicts with master
2. Call merge_agent_work for that story
3. run_squash_merge resolves conflicts (possibly incorrectly)
4. Fast-forwards master to the merge-queue commit BEFORE gates run
5. run_merge_quality_gates runs on master and finds broken code
6. Master is already broken
## Actual Result
Broken code (conflict markers, missing braces) lands on master. Mergemaster then fixes master directly, adding noise commits. All active worktrees pulling from master also break.
## Expected Result
Quality gates should run in the merge-queue worktree BEFORE fast-forwarding master. If gates fail, master should remain untouched.
## Acceptance Criteria
- [ ] Bug is fixed and verified

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---
name: "Remove 0 running count from Agents panel header"
---
# Story 143: Remove 0 running count from Agents panel header
## User Story
As a user, I want the Agents panel header to hide the running count when no agents are running, so that the UI is less cluttered when idle.
## Acceptance Criteria
- [ ] When no agents are running, "0 running" is NOT visible in the Agents panel header
- [ ] When one or more agents are running, "N running" IS visible in the Agents panel header
## Out of Scope
- Changing the running count display format when agents are running

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---
name: "Add build timestamp to frontend UI"
---
# Story 144: Add build timestamp to frontend UI
## User Story
As a developer, I want to see when the frontend was last built so I can tell whether it includes recent changes.
## Acceptance Criteria
- [ ] Inject a `__BUILD_TIME__` compile-time constant via `define` in `frontend/vite.config.ts`
- [ ] Display the build timestamp somewhere subtle in the UI (e.g. bottom corner, header tooltip, or footer)
- [ ] Timestamp should be human-readable (e.g. "Built: 2026-02-24 14:30")
## Out of Scope
- TBD

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---
name: "Persist chat history to localStorage across rebuilds"
---
# Story 145: Persist chat history to localStorage across rebuilds
## User Story
As a developer using the Story Kit web UI, I want my chat history to persist across page reloads and Vite HMR rebuilds, so that I don't lose my conversation context during development.
## Acceptance Criteria
- [ ] AC1: Chat messages are restored from localStorage on component mount (surviving page reload / HMR rebuild)
- [ ] AC2: Chat messages are saved to localStorage whenever the message history updates (via WebSocket `onUpdate` or user sending a message)
- [ ] AC3: Clearing the session via "New Session" button also removes persisted messages from localStorage
- [ ] AC4: localStorage quota errors are handled gracefully (fail silently with console.warn, never crash the app)
- [ ] AC5: Messages are stored under a key scoped to the project path so different projects have separate histories
## Out of Scope
- Server-side persistence of chat history
- Multi-tab synchronization of chat state
- Compression or size management of stored messages
- Persisting streaming content or loading state

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---
name: "Permission approval still returns wrong format - needs updatedInput not behavior allow"
---
# Bug 146: Permission approval still returns wrong format - needs updatedInput not behavior allow
## Description
Bug 130 changed prompt_permission from plain text to JSON, but used the wrong format. Claude Code permission-prompt-tool expects a union type: Approve = {updatedInput: {original tool input}}, Deny = {behavior: deny, message: string}. Current code at server/src/http/mcp.rs line 1642 returns {behavior: allow} which matches neither variant. Fix: change json!({behavior: allow}) to json!({updatedInput: tool_input}) where tool_input is already captured at line 1613. Also update the test at line 3076.
## How to Reproduce
1. Start server and open web UI
2. Chat with claude-code-pty agent
3. Ask it to do something requiring permission
4. Approve the permission dialog
5. Tool fails with Zod validation error about invalid_union
## Actual Result
prompt_permission returns behavior:allow on approval. Claude Code expects updatedInput with original input to approve.
## Expected Result
On approval, prompt_permission should return updatedInput containing the original tool input object.
## Acceptance Criteria
- [ ] Bug is fixed and verified

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name: "Activity indicator still only shows Thinking despite bug 140 fix"
---
# Bug 147: Activity indicator still only shows Thinking despite bug 140 fix
## Description
Bug 140 fixed the frontend display condition but activity labels still never appear. The full data path has been traced and the suspected failure point identified.
## End-to-End Data Path
### 1. Frontend display (FIXED by bug 140)
- `frontend/src/components/Chat.tsx` line 686: `{loading && (activityStatus != null || !streamingContent) && (`
- `frontend/src/components/Chat.tsx` line 697: `{activityStatus ?? "Thinking..."}`
- `frontend/src/components/Chat.tsx` line 204: `setActivityStatus(formatToolActivity(toolName))` — called by `onActivity` callback
### 2. WebSocket client receives event
- `frontend/src/api/client.ts` line 350: `if (data.type === "tool_activity") this.onActivity?.(data.tool_name)`
### 3. Server sends ToolActivity over WebSocket (WIRED CORRECTLY)
- `server/src/http/ws.rs` line 251-254: activity callback sends `WsResponse::ToolActivity { tool_name }`
- This callback is passed to `chat::chat()` as the `on_activity` closure
### 4. chat::chat passes callback to Claude Code provider
- `server/src/llm/chat.rs`: passes `on_activity` through to `claude_code::chat_stream`
- `server/src/llm/providers/claude_code.rs` line 47: `mut on_activity: A` parameter
- `server/src/llm/providers/claude_code.rs` line 70: creates internal `activity_tx` channel
- `server/src/llm/providers/claude_code.rs` line 94: drains channel and calls `on_activity(&name)`
### 5. PTY event processing (SUSPECTED FAILURE POINT)
- `server/src/llm/providers/claude_code.rs` line 327: `process_json_event()` dispatches parsed JSON
- Line 348-353: matches `"stream_event"` type → extracts inner `event` → calls `handle_stream_event()`
- `server/src/llm/providers/claude_code.rs` line 486: `handle_stream_event()` matches on event type
- Line 494-500: matches `"content_block_start"` with `content_block.type == "tool_use"` → sends to `activity_tx`
### 6. The problem
`handle_stream_event` only matches `content_block_start` — this is the **raw Anthropic streaming API format**. But Claude Code's `--output-format stream-json` may NOT emit raw Anthropic events wrapped in `stream_event`. It likely uses its own event types for tool calls (e.g. `tool_use_begin`, `tool_use`, or similar).
The existing `process_json_event` also matches `"assistant"` (line 355) and `"user"` (line 363) event types from stream-json, but these are complete messages — they arrive after the tool call is done, not when it starts. So there's no event being caught at tool-call-start time.
## Investigation Steps
1. Add logging in `process_json_event` (line 334) to print every `event_type` received from the PTY during a chat session with tool use
2. Identify which event type Claude Code emits when it starts a tool call
3. Add matching for that event type to fire `activity_tx.send(tool_name)`
## Key Files
- `server/src/llm/providers/claude_code.rs` line 327: `process_json_event` — event dispatcher
- `server/src/llm/providers/claude_code.rs` line 486: `handle_stream_event` — only handles Anthropic API format
- `server/src/http/ws.rs` line 251: activity callback wiring to WebSocket
- `frontend/src/components/Chat.tsx` line 203: `onActivity` handler that sets display state
## How to Reproduce
1. Rebuild both frontend and backend from master (which includes story 86 and bug 140)
2. Open web UI chat
3. Send a message that causes tool use (e.g. ask agent to read a file)
4. Watch the activity indicator
## Actual Result
Indicator always shows "Thinking..." and never changes to tool activity labels like "Reading file..." or "Executing command..."
## Expected Result
Indicator should cycle through tool activity labels as the agent calls tools
## Hints for the Coder
- **Check external docs**: The Claude Code CLI `--output-format stream-json` format may be documented at https://docs.anthropic.com or in the Claude Code repo. Search for the actual event schema before guessing.
- **Add logging as an intermediate step**: If unsure about the event format, add a `slog!` or `eprintln!` in `process_json_event` (line 334) to log every `event_type` received. Rebuild, run a web UI chat with tool use, and inspect the output to see exactly what events arrive.
- **Run the CLI directly**: You can run `claude -p "read /etc/hosts" --output-format stream-json` in a terminal to see the raw stream-json output and identify the event types for tool calls.
- **Don't assume the Anthropic API format**: The existing `content_block_start` matching was likely copied from the Anthropic provider. Claude Code's stream-json is a different format.
## Acceptance Criteria
- [ ] Activity indicator shows tool names (e.g. "Reading file...", "Executing command...") when the web UI agent calls tools
- [ ] Indicator still falls back to "Thinking..." when no tool activity is in progress
- [ ] Works for all tool types (Read, Write, Bash, Glob, Grep, etc.)

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---
name: "Interactive onboarding guides user through project setup after init"
---
# Story 148: Interactive onboarding guides user through project setup after init
## User Story
As a new Story Kit user, after the project structure has been scaffolded, I want a guided conversation that asks me about my project goals and tech stack, so that the specs are populated and I'm ready to write Story #1.
## Acceptance Criteria
- [ ] After scaffold completes and the user opens the chat UI, the agent detects empty/template specs and enters onboarding mode
- [ ] The agent asks the user what the project is about (goal, domain) and writes a populated specs/00_CONTEXT.md based on their answers
- [ ] The agent asks the user what tech stack they want (language, framework, build tools, test runner, linter) and writes a populated specs/tech/STACK.md based on their answers
- [ ] The agent updates script/test to invoke the project's actual test runner (e.g. cargo test, pytest, pnpm test)
- [ ] The agent updates project.toml component setup commands to match the chosen stack (e.g. pnpm install for a JS project, cargo check for Rust)
- [ ] After onboarding completes, the agent commits the populated specs and tells the user they're ready for Story #1
## Out of Scope
- TBD

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---
name: "Web UI does not update when agents are started or stopped"
---
# Bug 149: Web UI does not update when agents are started or stopped
## Description
Agent start/stop changes are in-memory HashMap mutations in the agent pool. No WatcherEvent is emitted for these changes, so the WebSocket never pushes an update to the frontend. The agent panel only refreshes on its polling interval, meaning agent swaps and new agent starts are invisible until the next poll.
Additionally, when an agent is assigned to a work item (e.g. a coder starts on a story), the pipeline board should reflect the change immediately — the work item should go from amber (unassigned) to green (agent working). Currently this requires a full page refresh.
The key insight is that agent assignment is an in-memory event, not a filesystem event, so the watcher won't catch it. The server needs to push agent state changes over WebSocket explicitly.
Fix options:
1. Emit a WatcherEvent (e.g. AgentStateChanged) when start_agent/stop_agent modifies the pool, and have the WebSocket handler forward it to the frontend
2. Or have the frontend subscribe to a dedicated agent-state WebSocket message type
Key files:
- server/src/agents.rs: start_agent / stop_agent — where the state change happens
- server/src/http/ws.rs: WebSocket handler that could forward agent state events
- frontend/src/components/AgentPanel.tsx: polling-based agent list refresh
- frontend pipeline board: wherever work item color (amber/green) is derived from agent assignment
## How to Reproduce
1. Open the web UI and look at the pipeline board
2. Start an agent on a story via MCP or the API
3. Observe the pipeline board — the work item stays amber until a full page refresh
## Actual Result
Agent panel and pipeline board do not update until the next polling interval or a full page refresh. Starting/stopping agents and agent assignment to work items are invisible in real-time.
## Expected Result
Agent panel and pipeline board should update immediately when agents are started, stopped, or assigned to work items.
## Acceptance Criteria
- [ ] Agent start/stop events are pushed over WebSocket to the frontend
- [ ] Pipeline board work items update color (amber → green) immediately when an agent is assigned
- [ ] No full page refresh required to see agent state changes

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---
name: Auto-focus Chat Input on Startup
---
# Story: Auto-focus Chat Input on Startup
## User Story
**As a** User
**I want** the cursor to automatically appear in the chat input box when the app starts
**So that** I can immediately start typing without having to click into the input field first.
## Acceptance Criteria
* [x] When the app loads and a project is selected, the chat input box should automatically receive focus
* [x] The cursor should be visible and blinking in the input field
* [x] User can immediately start typing without any additional clicks
* [x] Focus should be set after the component mounts
* [x] Should not interfere with other UI interactions
## Out of Scope
* Auto-focus when switching between projects (only on initial load)
* Remembering cursor position across sessions
* Focus management for other input fields
## Implementation Notes
* Use React `useEffect` hook to set focus on component mount
* Use a ref to reference the input element
* Call `inputRef.current?.focus()` after component renders
* Ensure it works consistently across different browsers
## Related Functional Specs
* Functional Spec: UI/UX

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---
name: "qa-2 agent never auto-assigned because pipeline_stage only matches exact qa"
---
# Bug 150: qa-2 agent never auto-assigned because pipeline_stage only matches exact qa
## Description
The `pipeline_stage()` function in `server/src/agents.rs` (line 154) determines an agent's pipeline role by parsing its **name** — there's no structured `stage` field in the agent config. This means `qa-2` falls through to `PipelineStage::Other` because it doesn't exactly match `"qa"`.
### Root Cause
`project.toml` agent config has `name` and `role` (freetext description), but no `stage` or `pipeline_role` field. The code guesses the pipeline stage from the name:
```rust
match agent_name {
"qa" => PipelineStage::Qa,
"mergemaster" => PipelineStage::Mergemaster,
name if name.starts_with("coder") => PipelineStage::Coder,
_ => PipelineStage::Other,
}
```
### The Fix
1. Add a `stage` field to `[[agent]]` in `project.toml` config schema. Valid values: `"coder"`, `"qa"`, `"mergemaster"`, `"other"`.
2. Update `ProjectConfig` / agent config deserialization in the server to parse the new field.
3. Replace `pipeline_stage(agent_name)` with a lookup from the agent's config `stage` field.
4. Update `project.toml` to add `stage` to all agents:
- supervisor: `stage = "other"`
- coder-1, coder-2, coder-opus: `stage = "coder"`
- qa, qa-2: `stage = "qa"`
- mergemaster: `stage = "mergemaster"`
5. Remove the name-based `pipeline_stage()` function entirely. The `stage` field is required.
### Key Files
- `server/src/agents.rs` line 154: `pipeline_stage()` — name-based matching
- `server/src/agents.rs` line 1728: `find_free_agent_for_stage()` — uses `pipeline_stage()`
- `server/src/config.rs` (or wherever `ProjectConfig` is defined): agent config deserialization
- `.story_kit/project.toml`: agent definitions
## How to Reproduce
1. Have multiple items in `3_qa/`
2. `qa` agent gets assigned to one
3. `qa-2` never gets assigned to the others
## Actual Result
`qa-2` is never auto-assigned. `pipeline_stage("qa-2")` returns `PipelineStage::Other`.
## Expected Result
`qa-2` should be recognized as a QA agent and auto-assigned to items in `3_qa/`.
## Acceptance Criteria
- [ ] Agent config in `project.toml` supports a `stage` field (`coder`, `qa`, `mergemaster`, `other`)
- [ ] `find_free_agent_for_stage` uses the config `stage` field instead of name parsing
- [ ] `qa-2` is correctly auto-assigned to QA work
- [ ] `stage` is a required field — server refuses to start if any agent is missing it
- [ ] The old name-based `pipeline_stage()` function is removed
- [ ] All existing agents in `project.toml` have `stage` set

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---
name: "Split archived into done and archived with time-based promotion"
---
# Story 151: Split archived into done and archived with time-based promotion
## User Story
As a developer watching work flow through the pipeline in my IDE, I want recently completed items separated from old ones, so that the folder view stays useful without being cluttered by dozens of ancient stories.
## Description
The `5_archived` folder has grown huge and clutters the IDE sidebar. Split it into two stages:
- `5_done`: recently completed work — visible in IDE, useful for watching flow
- `6_archived`: old work moved here automatically after 4 hours
The watcher should periodically check `5_done/` and move items older than 4 hours (based on file mtime) to `6_archived/`.
### Key Files
- `server/src/io/watcher.rs`: filesystem watcher — add periodic sweep of `5_done/`
- `server/src/agents.rs`: `move_story_to_archived` → rename to `move_story_to_done`, target `5_done/`
- All MCP tools and pipeline logic that reference `5_archived` need updating to use `5_done`
- Frontend pipeline display if it shows archived/done items
- `.story_kit/README.md`: update pipeline stage documentation
- Story 116's init scaffolding: `story-kit init` must create `5_done/` and `6_archived/` directories
- Any templates or scaffold code that creates the `.story_kit/work/` directory structure
## Acceptance Criteria
- [ ] `5_archived/` is renamed to `6_archived/`
- [ ] New `5_done/` directory is created and used as the immediate completion target
- [ ] Mergemaster, accept_story, and all pipeline functions move completed work to `5_done/` (not directly to archived)
- [ ] Watcher periodically sweeps `5_done/` and moves items older than 4 hours to `6_archived/`
- [ ] Existing items in old `5_archived/` are migrated to `6_archived/`
- [ ] Frontend pipeline display updated if applicable
- [ ] `.story_kit/README.md` updated to reflect the new pipeline stages
- [ ] `story-kit init` scaffolding creates `5_done/` and `6_archived/` (coordinate with story 116)
## Out of Scope
- TBD

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---
name: "Ollama not running kills the entire web UI"
---
# Bug 152: Ollama not running kills the entire web UI
## Description
The UI fetches Ollama models on load via /api/ollama/models (server/src/http/model.rs line 40). When Ollama is not running, the request fails and the error propagates in a way that kills the whole UI.
The server endpoint at server/src/http/model.rs should return an empty list instead of an error when Ollama is unreachable. Or the frontend should catch the error gracefully and just show no Ollama models in the dropdown.
## How to Reproduce
1. Stop Ollama (or never start it)
2. Open the web UI
3. Observe error: Request failed: error sending request for url (http://localhost:11434/api/tags)
## Actual Result
The entire web UI is broken. Nothing works.
## Expected Result
Ollama model fetch should fail silently or show an empty model list. The rest of the UI should work normally with Claude Code or Anthropic providers.
## Acceptance Criteria
- [ ] Bug is fixed and verified

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---
name: "Auto-assign broken after stage field was added to agent config"
---
# Bug 153: Auto-assign broken after stage field was added to agent config
## Description
Bug 150 changed agent pipeline role detection from name-based matching (pipeline_stage function) to a stage field in project.toml. The auto_assign_available_work function in server/src/agents.rs (line 1212) uses find_free_agent_for_stage (line 1728) to match agents to pipeline stages. After the stage field change, auto-assign stopped working — free coders are not picked up for items in 2_current/.
Likely causes:
- find_free_agent_for_stage still calls the old pipeline_stage() by name instead of reading the config stage field
- Or the PipelineStage enum comparison is failing due to a mismatch between config values and enum variants
- Or auto_assign_available_work is not being triggered after agent completion
Key files:
- server/src/agents.rs line 1212: auto_assign_available_work
- server/src/agents.rs line 1728: find_free_agent_for_stage
- server/src/config.rs: agent config with new stage field
- .story_kit/project.toml: stage values on each agent
## How to Reproduce
1. Have items in 2_current/ with free coders available
2. Wait for auto_assign_available_work to trigger
3. Free coders are not assigned to waiting items
## Actual Result
Free coders sit idle while items wait in current. Manual start_agent works fine.
## Expected Result
auto_assign_available_work should detect free coders and assign them to waiting items, using the new stage field from project.toml.
## Acceptance Criteria
- [ ] Bug is fixed and verified

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