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Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports.
Passed 14 of 19 test cases with the skill, and 6 of 19 without it.
and 6 more in the full report
9 fixed7 passed either way6 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
What is the default blocking timeout when using `wait_for_mission` on a running task?
| Checked | Without skill | With skill |
|---|---|---|
| States that the default timeout is 600 seconds | Missed | Passed |
The instructions your model reads when the skill loads.
Use this skill when you need to dispatch multiple Claude Code agents to work on coding tasks in parallel. Each agent runs in an isolated git worktree with full tooling.
Requires a running Claude DevFleet instance connected via MCP:
claude mcp add devfleet --transport http http://localhost:18801/mcp
User → "Build a REST API with auth and tests"
↓
plan_project(prompt) → project_id + mission DAG
↓
Show plan to user → get approval
↓
dispatch_mission(M1) → Agent 1 spawns in worktree
↓
M1 completes → auto-merge → auto-dispatch M2 (depends_on M1)
↓
M2 completes → auto-merge
↓
get_report(M2) → files_changed, what_done, errors, next_steps
↓
Report back to user
| Tool | Purpose |
|---|---|
plan_project(prompt) | AI breaks a description into a project with chained missions |
create_project(name, path?, description?) | Create a project manually, returns project_id |
create_mission(project_id, title, prompt, depends_on?, auto_dispatch?) | Add a mission. depends_on is a list of mission ID strings (e.g., ["abc-123"]). Set auto_dispatch=true to auto-start when deps are met. |
dispatch_mission(mission_id, model?, max_turns?) | Start an agent on a mission |
cancel_mission(mission_id) | Stop a running agent |
test cases passed, vs 6 / 19 without
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