القائمة
Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | claude-devfleet |
| description | Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports. |
| metadata | {"origin":"community"} |
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.
The DevFleet server is a separate project, not bundled with ECC. Install and run it from its repository first: https://github.com/LEC-AI/claude-devfleet
Then connect the running instance via MCP:
claude mcp add devfleet --transport http http://localhost:18801/mcp
Before first use, verify the process listening on port 18801 is the DevFleet binary you installed (see SECURITY.md on localhost MCP servers).
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)
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M2 completes → auto-merge
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get_report(M2) → files_changed, what_done, errors, next_steps
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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 |
wait_for_mission(mission_id, timeout_seconds?) | Block until a mission completes (see note below) |
get_mission_status(mission_id) | Check mission progress without blocking |
get_report(mission_id) | Read structured report (files changed, tested, errors, next steps) |
get_dashboard() | System overview: running agents, stats, recent activity |
list_projects() | Browse all projects |
list_missions(project_id, status?) | List missions in a project |
Note on
wait_for_mission: This blocks the conversation for up totimeout_seconds(default 600). For long-running missions, prefer polling withget_mission_statusevery 30–60 seconds instead, so the user sees progress updates.
plan_project(prompt="...") → returns project_id + list of missions with depends_on chains and auto_dispatch=true.dispatch_mission(mission_id=<first_mission_id>) on the root mission (empty depends_on). Remaining missions auto-dispatch as their dependencies complete (because plan_project sets auto_dispatch=true on them).get_mission_status(mission_id=...) or get_dashboard() to check progress.get_report(mission_id=...) when missions complete. Share highlights with the user.DevFleet runs up to 3 concurrent agents by default (configurable via DEVFLEET_MAX_AGENTS). When all slots are full, missions with auto_dispatch=true queue in the mission watcher and dispatch automatically as slots free up. Check get_dashboard() for current slot usage.
plan_project(prompt="...") → shows plan with missions and dependencies.depends_on).auto_dispatch=true).get_mission_status or get_dashboard() periodically until all missions reach a terminal state (completed, failed, or cancelled).get_report(mission_id=...) for each terminal mission — summarize successes and call out failures with errors and next steps.create_project(name="My Project") → returns project_id.create_mission(project_id=project_id, title="...", prompt="...", auto_dispatch=true) for the first (root) mission → capture root_mission_id.
create_mission(project_id=project_id, title="...", prompt="...", auto_dispatch=true, depends_on=["<root_mission_id>"]) for each subsequent task.dispatch_mission(mission_id=...) on the first mission to start the chain.get_report(mission_id=...) when done.create_project(name="...") → get project_id.create_mission(project_id=project_id, title="Implement feature", prompt="...") → get impl_mission_id.dispatch_mission(mission_id=impl_mission_id), then poll with get_mission_status until complete.get_report(mission_id=impl_mission_id) to review results.create_mission(project_id=project_id, title="Review", prompt="...", depends_on=[impl_mission_id], auto_dispatch=true) — auto-starts since the dependency is already met.get_dashboard() for agent slot availability before bulk dispatching.auto_dispatch=true if you want them to trigger automatically when dependencies complete. Without this flag, missions stay in draft status.Use after a complex task, failure, or when reviewing what was learned. Teaches how to write growth logs that extract reusable patterns — not diary entries.
Design a goal-oriented agent loop, and review it for the ways loops go wrong — spinning and burning tokens, Goodhart-gaming the verifier, or running a wrong answer to completion. Two actions: (1) WRITE a loop — gate whether to build it, define a machine-decidable goal, pick the loop type, pick a skeleton; (2) REVIEW a loop — run it past five failure modes plus decidability, boundaries, fallback, judge independence, and keep-judgment-with-the-human red lines. Use when designing an autonomous agent loop, or when you already have one and worry it will spin, cheat, or run a wrong answer to the end. Complements the mechanism-layer loop skills (autonomous-loops, continuous-agent-loop) by covering the judgment layer they don't. 中文触发：写 loop、设计 loop、做一个 loop、检查 loop 对不对、loop 体检、loop 会不会跑飞、可判定目标、五个崩法、plan build judge。English triggers: design an agent loop, write a loop, check a loop, loop review, prevent a runaway loop, goal-oriented loop, decidable goal, plan/build/judge.
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React Native and Expo app patterns — Expo Router navigation, state separation (server/client/route/form), TanStack Query data fetching with Zod, performant lists, NativeWind/StyleSheet styling, native APIs, and secure storage. Use when building or editing React Native / Expo screens, components, navigation, or data layers.
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