- Add `createTaskForAgent` tRPC mutation: resolves agent → task → phase, creates sibling task
- Add `cw task add <name> --agent-id <id>` CLI command
- Replace `{AGENT_ID}` and `{AGENT_NAME}` placeholders in writeInputFiles() before flushing
- Update docs/agent.md and docs/cli-config.md
285 lines
18 KiB
Markdown
285 lines
18 KiB
Markdown
# Agent Module
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`apps/server/agent/` — Agent lifecycle management, output parsing, multi-provider support, and account failover.
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## File Inventory
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| File | Purpose |
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|------|---------|
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| `types.ts` | Core types: `AgentInfo`, `AgentManager` interface, `SpawnOptions`, `StreamEvent` |
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| `manager.ts` | `MultiProviderAgentManager` — main orchestrator class |
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| `process-manager.ts` | `AgentProcessManager` — worktree creation, command building, detached spawn |
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| `output-handler.ts` | `OutputHandler` — JSONL stream parsing, completion detection, proposal creation, task dedup, task dependency persistence |
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| `file-tailer.ts` | `FileTailer` — watches output files, fires parser + raw content callbacks |
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| `file-io.ts` | Input/output file I/O: frontmatter writing, signal.json reading, tiptap conversion. Output files support `action` field (create/update/delete) for chat mode CRUD. Includes `writeErrandManifest()` for errand agent input files. |
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| `markdown-to-tiptap.ts` | Markdown to Tiptap JSON conversion using MarkdownManager |
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| `index.ts` | Public exports, `ClaudeAgentManager` deprecated alias |
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### Sub-modules
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| Directory | Purpose |
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|-----------|---------|
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| `providers/` | Provider registry, presets (7 providers), config types |
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| `providers/parsers/` | Provider-specific output parsers (Claude JSONL, generic line) |
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| `accounts/` | Account discovery, config dir setup, credential management, usage API |
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| `credentials/` | `AccountCredentialManager` — credential injection per account |
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| `lifecycle/` | `LifecycleController` — retry policy, signal recovery, missing signal instructions |
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| `prompts/` | Mode-specific prompt builders (execute, discuss, plan, detail, refine, chat, conflict-resolution, errand) + shared blocks (test integrity, deviation rules, git workflow, session startup, progress tracking) + inter-agent communication instructions. Conflict-resolution uses a minimal inline startup (pwd, git status, CLAUDE.md) instead of the full `SESSION_STARTUP`/`CONTEXT_MANAGEMENT` blocks. |
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## Key Flows
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### Spawning an Agent
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1. **tRPC procedure** calls `agentManager.spawn(options)`
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2. Manager generates alias (adjective-animal), creates DB record. Appends inter-agent communication and preview instructions unless `skipPromptExtras: true` (used by conflict-resolution agents to keep prompts lean).
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3. `AgentProcessManager.createProjectWorktrees()` — creates git worktrees at `agent-workdirs/<alias>/<project>/`. After creation, each project subdirectory is verified to exist; missing worktrees throw immediately to prevent agents running in the wrong directory.
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4. `file-io.writeInputFiles()` — writes `.cw/input/` with assignment files (initiative, pages, phase, task) and read-only context dirs (`context/phases/`, `context/tasks/`). Before flushing writes, replaces `{AGENT_ID}` and `{AGENT_NAME}` placeholders in all content with the agent's real ID and name.
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5. Provider config builds spawn command via `buildSpawnCommand()`
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6. `spawnDetached()` — launches detached child process with file output redirection
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7. `FileTailer` watches output file, fires `onEvent` (parsed stream events) and `onRawContent` (raw JSONL chunks) callbacks
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8. `onRawContent` → DB insert via `createLogChunkCallback()` → `agent:output` event emitted (single emission point)
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9. `OutputHandler.handleStreamEvent()` processes parsed events (session tracking, result capture — no event emission)
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10. DB record updated with PID, output file path, session ID
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11. `agent:spawned` event emitted
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### Completion Detection
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1. Polling detects process exit, `FileTailer.stop()` flushes remaining output
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2. `OutputHandler.handleCompletion()` triggered
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3. **Path resolution**: Uses `ActiveAgent.agentCwd` (recorded at spawn) to locate signal.json. Standalone agents run in a `workspace/` subdirectory under `agent-workdirs/<alias>/`, so the base `getAgentWorkdir()` path won't contain `.cw/output/signal.json`. Reconciliation and crash detection paths also probe for the `workspace/` subdirectory when `.cw/output` is missing at the base level.
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4. **Primary path**: Reads `.cw/output/signal.json` from agent worktree
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5. Signal contains `{ status: "done"|"questions"|"error", result?, questions?, error? }`
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6. Agent DB status updated accordingly (idle, waiting_for_input, crashed)
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7. For `done`: proposals created from structured output; `agent:stopped` emitted
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8. For `questions`: parsed and stored as `pendingQuestions`; `agent:waiting` emitted
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9. **Fallback**: If signal.json missing, lifecycle controller retries with instruction injection
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### Account Failover
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1. On usage-limit error, `markAccountExhausted(id, until)` called
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2. `findNextAvailable(provider)` returns least-recently-used non-exhausted account
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3. Agent re-spawned with new account's credentials
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4. `agent:account_switched` event emitted
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### Resume Flow
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1. tRPC `resumeAgent` called with `answers: Record<string, string>`
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2. Manager looks up agent's session ID and provider config
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3. `buildResumeCommand()` creates resume command with session flag
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4. `formatAnswersAsPrompt(answers)` converts answers to prompt text
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5. New detached process spawned, same worktree, incremented session number
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## Provider Configuration
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Providers defined in `providers/presets.ts`:
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| Provider | Command | Resume | Prompt Mode |
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|----------|---------|--------|-------------|
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| claude | `claude` | `--resume <id>` | native (`-p`) |
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| claude-code | `claude` | `--resume <id>` | native |
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| codex | `codex` | none | flag (`--prompt`) |
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| aider | `aider` | none | flag (`--message`) |
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| cline | `cline` | none | flag |
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| continue | `continue` | none | flag |
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| cursor-agent | `cursor` | none | flag |
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Each provider config specifies: `command`, `args`, `resumeStyle`, `promptMode`, `structuredOutput`, `sessionId` extraction, `nonInteractive` options.
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## Output Parsing
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The `OutputHandler` processes JSONL streams from Claude CLI:
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- `init` event → session ID extracted and persisted
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- `text_delta` events → no-op in handler (output streaming handled by DB log chunks)
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- `result` event → final result with structured data captured on `ActiveAgent`
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- Signal file (`signal.json`) → authoritative completion status
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**Output event flow**: `FileTailer.onRawContent()` → DB `insertChunk()` → `EventBus.emit('agent:output')`. This is the single emission point — no events from `handleStreamEvent()` or `processLine()`.
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For providers without structured output, the generic line parser accumulates raw text.
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## Credential Management
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`AccountCredentialManager` in `credentials/` handles OAuth token lifecycle:
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- `read()` — extracts `claudeAiOauth` from `.credentials.json`. Only `accessToken` is required; `refreshToken` and `expiresAt` may be null (setup tokens).
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- `isExpired()` — returns false when `expiresAt` is null (setup tokens never "expire" from our perspective).
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- `ensureValid()` — if expired and `refreshToken` exists, refreshes. If expired with no `refreshToken`, returns invalid with error.
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### Setup Tokens
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Setup tokens (from `claude setup-token`) are long-lived OAuth access tokens with no refresh token or expiry. Register via:
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```sh
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cw account add --token <token> --email user@example.com
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```
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Stored as `credentials: {"claudeAiOauth":{"accessToken":"<token>"}}` and `configJson: {"hasCompletedOnboarding":true}`.
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## Errand Agent Support
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### `sendUserMessage(agentId, message)`
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Delivers a user message directly to a running or idle errand agent without going through the conversations table. Used by the `errand.sendMessage` tRPC procedure.
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**Steps**: look up agent → validate status (`running`|`idle`) → validate `sessionId` → clear signal.json → update status to `running` → build resume command → stop active tailer/poll → spawn detached → start polling.
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**Key difference from `resumeForConversation`**: no `conversationResumeLocks`, no conversations table entry, raw message passed as resume prompt.
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### `writeErrandManifest(options)`
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Writes errand input files to `<agentWorkdir>/.cw/input/`:
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- `errand.md` — YAML frontmatter with `id`, `description`, `branch`, `project`
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- `manifest.json` — `{ errandId, agentId, agentName, mode: "errand" }` (no `files`/`contextFiles` arrays)
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- `expected-pwd.txt` — the agent workdir path
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Written in order: `errand.md` first, `manifest.json` last (same discipline as `writeInputFiles`).
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### `buildErrandPrompt(description)`
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Builds the initial prompt for errand agents. Exported from `prompts/errand.ts` and re-exported from `prompts/index.ts`. The prompt instructs the agent to make only the changes needed for the description and write `signal.json` when done.
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## Auto-Resume for Conversations
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When Agent A asks Agent B a question via `cw ask` and Agent B is idle, the conversation router automatically resumes Agent B's session. This mirrors the `resumeForCommit()` pattern.
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### Flow
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1. `createConversation` tRPC procedure creates the conversation record
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2. Target resolution prefers `running` agents, falls back to `idle` (previously only matched `running`)
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3. After creation, checks if target agent is idle → calls `agentManager.resumeForConversation()`
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4. Agent resumes with a prompt to: answer via `cw answer`, drain pending conversations via `cw listen`, then complete
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### Guards
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- Agent must be `idle` status with a valid `sessionId`
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- Provider must support resume (`resumeStyle !== 'none'`)
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- Worktree must still exist (`existsSync` check)
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- In-memory `conversationResumeLocks` Set prevents double-resume race when multiple conversations arrive simultaneously
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- Resume failure is caught and logged — conversation is always created even if resume fails
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## Auto-Cleanup & Commit Retries
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After an agent completes (status → `idle`), `tryAutoCleanup` checks if its project worktrees have uncommitted changes:
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1. `CleanupManager.getDirtyWorktreePaths()` runs `git status --porcelain` in each project subdirectory (not the parent `agent-workdirs/<alias>/` dir), returns `{ name, absPath }[]`
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2. If all clean → worktrees and logs removed immediately
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3. If dirty → `resumeForCommit()` resumes the agent's session with a prompt listing **absolute paths** to dirty subdirectories, using `git add -u` (tracked files only) to avoid staging unrelated files
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4. The agent `cd`s into each listed absolute path and commits tracked changes only
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5. On next completion, cleanup runs again. `MAX_COMMIT_RETRIES` (1) limits retries — after that the workdir is left in place with a warning
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The retry counter is cleaned up on: successful removal, max retries exceeded, or unexpected error. It is **not** cleaned up when a commit retry is successfully launched (so the counter persists across the retry cycle).
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## Log Chunks
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Agent output is persisted to `agent_log_chunks` table and drives all live streaming:
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- `onRawContent` callback fires for every raw JSONL chunk from `FileTailer`
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- DB insert → `agent:output` event emission (single source of truth for UI)
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- No FK to agents — survives agent deletion
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- Session tracking: spawn=1, resume=previousMax+1
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- Read path (`getAgentOutput` tRPC): returns timestamped chunks `{ content, createdAt }[]` from DB
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- Live path (`onAgentOutput` subscription): listens for `agent:output` events (client stamps with `Date.now()`)
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- Frontend: initial query loads timestamped chunks, subscription accumulates live chunks, both parsed via `parseAgentOutput()` which accepts `TimestampedChunk[]`
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- Timestamps displayed inline (HH:MM:SS) on text, tool_call, system, and session_end messages
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## Inter-Agent Communication
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Agents can communicate with each other via the `conversations` table, coordinated through CLI commands.
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### Prompt Integration
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`buildInterAgentCommunication(agentId, mode)` function in `prompts/shared.ts` generates per-agent communication instructions. Called in `manager.ts` after agent record creation — the actual agent ID is injected directly into the prompt (no manifest.json indirection).
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**Mode-aware branching:**
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- **Planning modes** (`plan`, `refine`): Minimal block — just the agent ID and `cw ask` syntax for emergencies. These agents define high-level structure, not implementation details, so real-time coordination is almost never needed.
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- **Execution + coordination modes** (`execute`, `detail`, `discuss`, `verify`, `merge`, `review`): Full protocol including:
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1. Commands table with accurate CLI behavior descriptions
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2. Numbered shell recipe for background listener lifecycle (start → check → answer → restart → cleanup)
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3. Targeting guidance (`--agent-id` vs `--task-id` vs `--phase-id`)
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4. Decision criteria: when to ask (uncommitted interfaces, shared file conflicts) and when NOT to ask (answer in codebase, answer in input files, not blocked, confirming approach)
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5. Good/bad examples using `<example label>` pattern
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6. Answering guidelines (be specific — include code snippets, file paths, type signatures)
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### Agent Identity
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`manifest.json` includes `agentId` and `agentName` fields. The manager passes these from the DB record after agent creation. The agent ID is also injected directly into the prompt's communication instructions.
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### CLI Commands
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**`cw listen --agent-id <id>`**
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- Subscribes to `onPendingConversation` SSE subscription, prints first pending as JSON, exits with code 0
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- First yields any existing pending conversations from DB, then listens for `conversation:created` events
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- Output: `{ conversationId, fromAgentId, question, phaseId?, taskId? }`
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**`cw ask <question> --from <agentId> --agent-id|--task-id|--phase-id <target>`**
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- Creates conversation, subscribes to `onConversationAnswer` SSE, prints answer text to stdout when answered
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- Target resolution: `--agent-id` (direct), `--task-id` (find agent running task), `--phase-id` (find agent in phase)
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**`cw answer <answer> --conversation-id <id>`**
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- Calls `answerConversation`, prints `{ conversationId, status: "answered" }`
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## Prompt Architecture
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Mode-specific prompts in `prompts/` use XML tags as top-level structural delimiters, with markdown formatting inside tags. This separates first-order instructions from second-order content (task descriptions, examples, templates) per Anthropic best practices. The old `apps/server/agent/prompts.ts` (flat markdown) has been deleted.
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### XML Tag Structure
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All prompts follow a consistent tag ordering:
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1. `<role>` — agent identity and mode
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2. `<task>` — dynamic task content (execute mode only)
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3. `<input_files>` — file format documentation
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4. `<codebase_exploration>` — codebase grounding instructions (architect modes only)
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5. `<output_format>` — what to produce, file paths, frontmatter
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6. `<id_generation>` — ID creation via `cw id`
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7. `<signal_format>` — completion signaling
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8. `<session_startup>` — startup verification steps
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9. Mode-specific tags (see below)
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10. Rules/constraints tags
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11. `<progress_tracking>` / `<context_management>`
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12. `<definition_of_done>` — completion checklist
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13. `<workspace>` — workspace layout (appended by manager)
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14. `<inter_agent_communication>` — per-agent CLI instructions (appended by manager)
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### Shared Blocks (`prompts/shared.ts`)
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| Constant / Function | XML Tag | Content |
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|---------------------|---------|---------|
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| `SIGNAL_FORMAT` | `<signal_format>` | Done/questions/error via `.cw/output/signal.json` |
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| `INPUT_FILES` | `<input_files>` | Manifest, assignment files, context files |
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| `ID_GENERATION` | `<id_generation>` | `cw id` usage for generating entity IDs |
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| `TEST_INTEGRITY` | `<test_integrity>` | No self-validating tests, no assertion mutation, no skipping, independent tests, full suite runs |
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| `SESSION_STARTUP` | `<session_startup>` | Confirm working directory, check git state, establish green test baseline, read assignment |
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| `PROGRESS_TRACKING` | `<progress_tracking>` | Maintain `.cw/output/progress.md` after each commit — survives context compaction |
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| `DEVIATION_RULES` | `<deviation_rules>` | Typo→fix, bug→fix if small, missing dep→coordinate, architectural mismatch→STOP |
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| `GIT_WORKFLOW` | `<git_workflow>` | Specific file staging (no `git add .`), no force-push, check status first |
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| `CODEBASE_EXPLORATION` | `<codebase_exploration>` | Architect-mode codebase grounding: read project docs, explore structure, check existing patterns, use subagents for parallel exploration |
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| `CONTEXT_MANAGEMENT` | `<context_management>` | Parallel file reads, cross-reference to progress tracking |
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| `buildInterAgentCommunication()` | `<inter_agent_communication>` | Per-agent CLI instructions for `cw listen`, `cw ask`, `cw answer` |
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### Mode-Specific Tags
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| Mode | File | Mode-Specific Tags |
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|------|------|--------------------|
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| **execute** | `execute.ts` | `<task>`, `<execution_protocol>`, `<anti_patterns>`, `<scope_rules>` |
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| **plan** | `plan.ts` | `<phase_design>`, `<dependencies>`, `<file_ownership>`, `<specificity>`, `<existing_context>` |
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| **detail** | `detail.ts` | `<task_body_requirements>`, `<file_ownership>`, `<task_sizing>`, `<existing_context>` |
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| **discuss** | `discuss.ts` | `<analysis_method>`, `<question_quality>`, `<decision_quality>`, `<question_categories>`, `<rules>` |
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| **refine** | `refine.ts` | `<improvement_priorities>`, `<rules>` |
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| **chat** | `chat.ts` | `<chat_history>`, `<instruction>` — iterative refinement loop, uses action field (create/update/delete) in output files, signals "questions" after each change to stay alive |
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Examples within mode-specific tags use `<examples>` > `<example label="good">` / `<example label="bad">` nesting.
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### Execute Prompt Dispatch
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`buildExecutePrompt(taskDescription?)` accepts an optional task description wrapped in a `<task>` tag. The dispatch manager (`apps/server/dispatch/manager.ts`) wraps `task.description || task.name` in `buildExecutePrompt()` so execute agents receive full system context alongside their task. The `<workspace>` and `<inter_agent_communication>` blocks are appended by the agent manager at spawn time.
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## Prompt Placeholders
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`writeInputFiles()` replaces these tokens in all input file content before writing:
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| Placeholder | Replaced With |
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|-------------|---------------|
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| `{AGENT_ID}` | The agent's database ID |
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| `{AGENT_NAME}` | The agent's human-readable name |
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Use in phase detail text or task descriptions to give agents self-referential context, e.g.: *"Report issues via `cw task add --agent-id {AGENT_ID}`"*
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