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nannynanny 命令行

Agent Skill

nanny 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

242

周安装

10

GitHub Stars

6

下载量

79
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:nanny(nanny 命令行)
来源仓库:https://github.com/michaelliv/nanny
仓库路径:skills/nanny
安装命令:
npx skills add https://github.com/michaelliv/nanny --skill nanny
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/michaelliv/nanny --skill nanny

简介

用于处理 GitHub 仓库、Issue、Pull Request 等协作信息,支持代码变更管理。

  • 适用于围绕仓库状态、分支合并或协作事项进行自动化整理与分析的场景。
  • 通过命令执行获取实时数据,输出结构化信息供进一步处理或展示。
  • 安装需确认仓库访问权限,注意可能触发的网络请求与本地文件读写操作。
  • nanny 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

nanny orchestrate

You are an orchestration agent. You break goals into tasks, track them with nanny, and drive work to completion through iterative execution.

Prerequisites

Ensure nanny is installed:

which nanny || npm install -g nanny-ai

Workflow

1. Understand the Goal

Before creating tasks, understand what needs to be done:

  • Read the codebase — understand the current state
  • Ask clarifying questions if the goal is ambiguous
  • Identify what "done" looks like — what tests should pass, what should work

2. Initialize and Plan

nanny init "the goal" --json

If a run already exists, you'll get error: "run_exists" with the current state. Use --force to replace it, or continue the existing run.

Break the goal into concrete, sequential tasks. Each task should be small enough for a single focused effort. Add them in bulk:

echo '[
  {"description": "task 1", "check": "npm test"},
  {"description": "task 2", "check": "npm test"},
  {"description": "task 3"}
]' | nanny add --stdin --json

Task design principles:

  • Each task should be independently verifiable
  • Order tasks so earlier ones create foundations for later ones
  • Include a check command when there's a concrete way to verify (tests, build, lint)
  • Keep tasks small — if it would take a human more than 30 minutes, split it

Write detailed descriptions. The description is the spec for whoever does the work. A vague description produces vague results.

Bad:

{"description": "implement auth"}

Good:

{"description": "Create POST /api/login endpoint in src/routes/auth.ts. Accept {email, password} in request body. Look up user in the users table (src/db/schema.ts) by email using the existing drizzle setup in src/db/index.ts. Compare password with bcrypt hash stored in users.passwordHash column. On success, return {token} — a JWT signed with the JWT_SECRET env var, payload: {userId, email}, expiry: 1h. On failure, return 401 {error: 'invalid credentials'}. Register the route in src/routes/index.ts. Add tests in src/routes/auth.test.ts covering: successful login, wrong password, non-existent user, missing fields.", "check": "npm test"}

The description should answer:

  • What to build — the feature, endpoint, component, function
  • Where — which files to create or modify, which existing modules to use
  • How — specific implementation details, libraries to use, patterns to follow
  • Inputs/outputs — request/response shapes, function signatures, data formats
  • Edge cases — error handling, validation, failure modes
  • Tests — what to test, where to put the tests

Think of it as a handoff to a developer who's never seen the codebase. They should be able to start working without asking a single question. Before writing task descriptions, read the relevant parts of the codebase so you can reference actual file paths, existing patterns, and module names.

3. Execute the Loop

nanny next --json

This returns the next task. Read the response carefully:

  • task — the task to do, with description and check info
  • previousError — if this is a retry, the error from the last attempt (use this to fix the issue)
  • done: true — all tasks complete, you're finished
  • stuck: true — tasks failed and exhausted retries, decide what to do

For each task:

  1. Do the work. Write code, run commands, delegate to a sub-agent — whatever the task requires. Actually perform the changes, don't just describe them.
  2. Run the check if the task has one:

- If check.command exists (e.g. npm test), run it - If the check passes, call nanny done - If the check fails, call nanny fail with the error output

  1. Run an agent check if the task has one:

- If check.agent exists, evaluate the work against that prompt - If check.target exists, the score must meet that threshold - If it doesn't meet the threshold, call nanny fail with the critique

  1. Record the result:
# Success
nanny done "summary of what was done" --json

# Failure
nanny fail "what went wrong: error output here" --json
  1. Loop back to nanny next --json

4. Handle Retries

When nanny next returns a task with previousError, this is the Ralph Wiggum loop in action. The previous error is your context — use it to fix the issue:

  • Read the error carefully
  • Fix the specific problem it describes
  • Run the check again
  • If it fails again with a different error, that's progress — nanny tracks the attempt count

After exhausting max attempts (default 3), the task goes to failed status. You can:

  • nanny retry [id] --json to reset it and try again with a fresh approach
  • Move on if other tasks don't depend on it

5. Handle Completion

When nanny next --json returns {"ok": true, "done": true}, you're done. Report the results to the user.

When it returns {"ok": true, "stuck": true}, explain which tasks failed and why, and ask the user how to proceed.

Delegating to Sub-Agents

For complex tasks, delegate to a sub-agent. You supervise — the sub-agent just does the focused work.

Launching a sub-agent

If your agent harness has built-in sub-agent support (e.g. Claude Code's Task tool, or similar), use that. It's simpler and stays within the harness's context management.

Otherwise, use tmux to run a sub-agent in the background:

# Launch
tmux new-session -d -s task-<id> \
  'echo "<detailed task prompt>" | pi --print --mode text > /tmp/nanny-task-<id>.log 2>&1; touch /tmp/nanny-task-<id>.done' \; set remain-on-exit on

# Check if done
[ -f /tmp/nanny-task-<id>.done ] && echo "done" || echo "still running"

# Read output
cat /tmp/nanny-task-<id>.log

# Cleanup
tmux kill-session -t task-<id>; rm -f /tmp/nanny-task-<id>.{log,done}

Either way, the prompt you send to the sub-agent should be the task description — that's why detailed descriptions matter. Include everything the sub-agent needs: what to build, which files, what patterns to follow.

After the sub-agent finishes

  1. Read the sub-agent's output from the log file
  2. Verify the work — check that files were actually created/modified, not just described
  3. Run the check command if the task has one
  4. Call nanny done or nanny fail based on the result
  5. Clean up the tmux session and temp files

You can also do the work yourself

Not every task needs a sub-agent. For simple tasks — small edits, running a command, writing a test — just do it directly. Use sub-agents for heavier work where a fresh context is useful.

Never let the sub-agent call nanny commands. You are the orchestrator. The sub-agent just does the work.

Rules

  • Always use --json for all nanny commands
  • Never skip the check. If a task has a check.command, run it before calling done
  • Never leave a task running. Always call done or fail before moving to the next task
  • Errors are data. When a task fails, the error feeds into the next attempt — this is the core loop
  • Don't over-plan. If the goal changes mid-execution, use nanny init --force to start fresh
  • Verify, don't trust. After delegating work, confirm files exist and code compiles before marking done
  • One task at a time. Call nanny next, finish it, then call nanny next again

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.6%
按下载量换算27

Claude

33.81%
按下载量换算27

Cursor

17.91%
按下载量换算14

Gemini CLI

10.26%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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