Add decompose + orchestrate skills with operational improvements
New skills for container agent task orchestration: - /decompose: break tasks into subtasks with dependency graph, write .agent-tasks.json - /orchestrate: check task state, launch container agents in git worktrees, poll for completion Updated with learnings from first real run (agent-runtimes M3, 9 tasks): - Prompts must end with "run pytest and fix failures" - State import conventions explicitly in prompts - Warn about uncommitted files before decomposing (worktrees need committed content) - Copy dependency outputs into downstream worktrees before launching Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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name: decompose
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description: >
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Decompose a task into subtasks with dependencies. Writes .agent-tasks.json for orchestration
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by container agents. Use /decompose followed by a task description or invoke mid-conversation.
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user_invocable: true
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allowed-tools: Read, Write, Edit, Glob, Grep, Bash(date *), Bash(cat *), Bash(hostname *), Bash(jq *), Bash(ls *), Bash(head *)
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---
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# /decompose Skill
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<command-name>decompose</command-name>
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You are decomposing a task into subtasks that can be executed by container agents in parallel.
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## Pre-gathered context
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### Current date
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!`date +%Y-%m-%dT%H:%M:%S`
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### Hostname
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!`hostname`
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### Existing task state
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!`cat .agent-tasks.json 2>/dev/null || echo "No task state file yet"`
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### Project context
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!`cat CLAUDE.md 2>/dev/null | head -100 || echo "No CLAUDE.md"`
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!`cat SPEC.md 2>/dev/null | head -50 || echo "No SPEC.md"`
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!`ls spec/ 2>/dev/null || echo "No spec directory"`
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## Instructions
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### Step 1: Understand the task
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Read `$ARGUMENTS` for the task description. If empty, ask the user what task to decompose.
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Also read the current conversation context — the user may have been discussing the task before invoking this skill.
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Read any relevant project files (PLAN.md, SPEC.md, spec/, CLAUDE.md) to understand the project structure and what work is needed.
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### Step 2: Decompose into subtasks
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Break the task into **independently executable subtasks**. Each subtask must be:
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- **Self-contained**: A container agent with access to the project can complete it without human input
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- **Scoped**: One clear deliverable (a spec file, a test file, an implementation file)
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- **Testable**: Success can be verified (file exists, tests pass, etc.)
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For each subtask, determine:
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- A short unique ID (e.g., `spec-harness`, `test-composition`, `impl-resolver`)
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- A human-readable name
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- Which other subtasks it depends on (by ID)
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- The full prompt that a container agent would receive
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- Which project files it needs to read
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- Which files it will create or modify
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**Guidelines:**
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- Prefer many small tasks over few large tasks
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- Tasks that can run in parallel SHOULD NOT depend on each other
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- Include "read these files first" in each task's prompt
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- Be explicit about what output is expected (file paths, test names)
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- **End every prompt with:** "Run `pytest tests/ -v --tb=short` and fix any failures before finishing. Write a session log to memory/log/ when done."
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- **State import conventions explicitly** in prompts — e.g., "Use `from module import X`, not `from .module import X`" when source dirs aren't packages
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- **Before writing .agent-tasks.json, warn the user to commit WIP** if there are untracked/uncommitted files that agents will need. Worktrees only see committed content.
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### Step 3: Present the task graph
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Show the user the decomposition as a dependency graph:
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```
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task-a (no deps) ─┐
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task-b (no deps) ─┼─► task-d (depends: a, b)
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task-c (no deps) ─┘ │
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▼
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task-e (depends: d)
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```
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Also show a table:
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| ID | Name | Depends On | Writes | Est. Complexity |
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|----|------|-----------|--------|-----------------|
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| ... | ... | ... | ... | low/medium/high |
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### Step 4: Get user approval
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Ask the user:
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1. Does the decomposition look right? They may want to merge, split, or reorder tasks.
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2. **How many concurrent agents should run?** Suggest a number based on the task graph width (max parallel tasks at any level). Note that each agent uses subscription tokens — more agents = faster but uses allocation quicker.
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### Step 5: Write the task state file
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Once approved, write `.agent-tasks.json` in the project root:
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```json
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{
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"created_at": "<ISO timestamp>",
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"project": "<project name from directory>",
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"description": "<original task description>",
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"max_concurrent": <user-approved number>,
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"tasks": {
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"<task-id>": {
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"name": "<human readable name>",
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"prompt": "<full prompt for container agent>",
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"depends_on": ["<task-id>", ...],
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"reads": ["<file paths the agent should read>"],
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"writes": ["<file paths the agent will create/modify>"],
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"status": "pending",
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"branch": null,
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"worktree": null,
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"host": null,
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"container_id": null,
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"started_at": null,
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"completed_at": null,
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"exit_code": null,
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"error": null
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}
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}
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}
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```
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**Status values:** `pending`, `running`, `completed`, `failed`, `blocked`
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**Worktree fields:**
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- `branch`: The git branch name for this task (e.g., `agent/<task-id>`)
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- `worktree`: The worktree path (e.g., `.worktrees/<task-id>`)
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Tell the user: "Task state written to `.agent-tasks.json`. Run `/orchestrate` to start executing tasks, or `/loop 2m /orchestrate` to auto-poll."
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