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Agent Skill · 研究检索

autopilot(autopilot 搜索)

autopilot 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

autopilot 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 37,302。

总安装 1,763周安装 72GitHub Stars 26,833下载 570核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:autopilot(autopilot 搜索)
来源仓库:https://github.com/yeachan-heo/oh-my-codex
仓库路径:skills/autopilot
安装命令:
npx skills add https://github.com/yeachan-heo/oh-my-codex --skill autopilot
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/yeachan-heo/oh-my-codex --skill autopilot

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。autopilot 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合根据关键词或任务场景快速定位候选结果。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围和维护状态。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。注意是否会触发联网、命令执行或文件读写。

来源仓库内路径:skills/autopilot

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/yeachan-heo/oh-my-codex --skill autopilot;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

autopilot 怎么安装?

在终端执行 npx skills add https://github.com/yeachan-heo/oh-my-codex --skill autopilot。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

autopilot 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

autopilot 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

autopilot 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

autopilot 用的人多吗?

公开数据是累计安装 1,763 次,近一周安装 72 次,下载 570 次,GitHub 26,833 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

autopilot 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 26,833 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
autopilot

autopilot 搜索 · 本页

1,76326,833调用外部服务未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

<Use_When>

  • User wants end-to-end autonomous execution from an idea to working code
  • User says "autopilot", "auto pilot", "autonomous", "build me", "create me", "make me", "full auto", "handle it all", or "I want a/an..."
  • Task requires multiple phases: planning, coding, testing, and validation
  • User wants hands-off execution and is willing to let the system run to completion </Use_When>

<Do_Not_Use_When>

  • User wants to explore options or brainstorm -- use plan skill instead
  • User says "just explain", "draft only", or "what would you suggest" -- respond conversationally
  • User wants a single focused code change -- use ralph or delegate to an executor agent
  • User wants to review or critique an existing plan -- use plan --review
  • Task is a quick fix or small bug -- use direct executor delegation </Do_Not_Use_When>

<Why_This_Exists> Most non-trivial software tasks require coordinated phases: understanding requirements, designing a solution, implementing in parallel, testing, and validating quality. Autopilot orchestrates all of these phases automatically so the user can describe what they want and receive working code without managing each step. </Why_This_Exists>

<Execution_Policy>

  • Each phase must complete before the next begins
  • Parallel execution is used within phases where possible (Phase 2 and Phase 4)
  • QA cycles repeat up to 5 times; if the same error persists 3 times, stop and report the fundamental issue
  • Validation requires approval from all reviewers; rejected items get fixed and re-validated
  • Cancel with /cancel at any time; progress is preserved for resume
  • If a deep-interview spec exists, use it as high-clarity phase input instead of re-expanding from scratch
  • If input is too vague for reliable expansion, offer/trigger $deep-interview first
  • Do not enter expansion/planning/execution-heavy phases until pre-context grounding exists; if fast execution is forced, proceed only with explicit risk notes
  • Apply the shared workflow guidance pattern: concise, evidence-dense progress and completion reporting, local overrides for the active workflow branch, persistent inspection/verification while the workflow depends on it, and automatic continuation for safe reversible steps. Ask only for material, destructive, or preference-dependent branches. </Execution_Policy>
  1. Phase 0 - Expansion: Turn the user's idea into a detailed spec

- If .omx/specs/deep-interview-*.md exists for this task: reuse it and skip redundant expansion work - If prompt is highly vague: route to $deep-interview for Socratic ambiguity-gated clarification - Analyst (THOROUGH tier): Extract requirements - Architect (THOROUGH tier): Create technical specification - Output: .omx/plans/autopilot-spec.md

  1. Phase 1 - Planning: Create an implementation plan from the spec

- Architect (THOROUGH tier): Create plan (direct mode, no interview) - Critic (THOROUGH tier): Validate plan - Output: .omx/plans/autopilot-impl.md

  1. Phase 2 - Execution: Implement the plan using Ralph + Ultrawork

- LOW-tier executor/search roles: Simple tasks - STANDARD-tier executor roles: Standard tasks - THOROUGH-tier executor/architect roles: Complex tasks - Run independent tasks in parallel

  1. Phase 3 - QA: Cycle until all tests pass (UltraQA mode)

- Build, lint, test, fix failures - Repeat up to 5 cycles - Stop early if the same error repeats 3 times (indicates a fundamental issue)

  1. Phase 4 - Validation: Multi-perspective review in parallel

- Architect: Functional completeness - Security-reviewer: Vulnerability check - Code-reviewer: Quality review - All must approve; fix and re-validate on rejection

  1. Phase 5 - Cleanup: Clear all mode state via OMX MCP tools on successful completion

- state_clear({mode: "autopilot"}) - state_clear({mode: "ralph"}) - state_clear({mode: "ultrawork"}) - state_clear({mode: "ultraqa"}) - Or run /cancel for clean exit

<Tool_Usage>

  • Before first MCP tool use, call ToolSearch("mcp") to discover deferred MCP tools
  • Use ask_codex with agent_role: "architect" for Phase 4 architecture validation
  • Use ask_codex with agent_role: "security-reviewer" for Phase 4 security review
  • Use ask_codex with agent_role: "code-reviewer" for Phase 4 quality review
  • Agents form their own analysis first, then consult Codex for cross-validation
  • If ToolSearch finds no MCP tools or Codex is unavailable, proceed without it -- never block on external tools </Tool_Usage>

State Management

Use omx_state MCP tools for autopilot lifecycle state.

  • On start: state_write({mode: "autopilot", active: true, current_phase: "expansion", started_at: "<now>", state: {context_snapshot_path: "<snapshot-path>"}})
  • On phase transitions: state_write({mode: "autopilot", current_phase: "planning"}) state_write({mode: "autopilot", current_phase: "execution"}) state_write({mode: "autopilot", current_phase: "qa"}) state_write({mode: "autopilot", current_phase: "validation"})
  • On completion: state_write({mode: "autopilot", active: false, current_phase: "complete", completed_at: "<now>"})
  • On cancellation/cleanup: run $cancel (which should call state_clear(mode="autopilot"))

Scenario Examples

Good: The user says continue after the workflow already has a clear next step. Continue the current branch of work instead of restarting or re-asking the same question.

Good: The user changes only the output shape or downstream delivery step (for example make a PR). Preserve earlier non-conflicting workflow constraints and apply the update locally.

Bad: The user says continue, and the workflow restarts discovery or stops before the missing verification/evidence is gathered.

<Escalation_And_Stop_Conditions>

  • Stop and report when the same QA error persists across 3 cycles (fundamental issue requiring human input)
  • Stop and report when validation keeps failing after 3 re-validation rounds
  • Stop when the user says "stop", "cancel", or "abort"
  • If requirements were too vague and expansion produces an unclear spec, pause and redirect to $deep-interview before proceeding </Escalation_And_Stop_Conditions>

<Final_Checklist>

  • All 5 phases completed (Expansion, Planning, Execution, QA, Validation)
  • All validators approved in Phase 4
  • Tests pass (verified with fresh test run output)
  • Build succeeds (verified with fresh build output)
  • State files cleaned up
  • User informed of completion with summary of what was built </Final_Checklist>

Optional settings in ~/.codex/config.toml:

[omx.autopilot]
maxIterations = 10
maxQaCycles = 5
maxValidationRounds = 3
pauseAfterExpansion = false
pauseAfterPlanning = false
skipQa = false
skipValidation = false

Resume

If autopilot was cancelled or failed, run /autopilot again to resume from where it stopped.

Recommended Clarity Pipeline

For ambiguous requests, prefer:

deep-interview -> ralplan -> autopilot
  • deep-interview: ambiguity-gated Socratic requirements
  • ralplan: consensus planning (planner/architect/critic)
  • autopilot: execution + QA + validation

Best Practices for Input

  1. Be specific about the domain -- "bookstore" not "store"
  2. Mention key features -- "with CRUD", "with authentication"
  3. Specify constraints -- "using TypeScript", "with PostgreSQL"
  4. Let it run -- avoid interrupting unless truly needed

Pipeline Orchestrator (v0.8+)

Autopilot can be driven by the configurable pipeline orchestrator (src/pipeline/), which sequences stages through a uniform PipelineStage interface:

RALPLAN (consensus planning) -> team-exec (Codex CLI workers) -> ralph-verify (architect verification)

Pipeline configuration options:

[omx.autopilot.pipeline]
maxRalphIterations = 10    # Ralph verification iteration ceiling
workerCount = 2            # Number of Codex CLI team workers
agentType = "executor"     # Agent type for team workers

The pipeline persists state via pipeline-state.json and supports resume from the last incomplete stage. See src/pipeline/orchestrator.ts for the full API.

Troubleshooting

Stuck in a phase? Check TODO list for blocked tasks, run state_read({mode: "autopilot"}), or cancel and resume.

QA cycles exhausted? The same error 3 times indicates a fundamental issue. Review the error pattern; manual intervention may be needed.

Validation keeps failing? Review the specific issues. Requirements may have been too vague -- cancel and provide more detail.

平台分布

Codex

36.44%
按下载量换算208

Claude

29.34%
按下载量换算167

Cursor

19.93%
按下载量换算114

Gemini CLI

9.46%
按下载量换算54

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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