Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/an8079/take-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/an8079/take-skills/takes-autopilot)<a href="https://agentmods.dev/commands/an8079/take-skills/takes-autopilot"><img src="https://agentmods.dev/badge/commands/an8079/take-skills/takes-autopilot/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/an8079/take-skills/takes-autopilot"><img src="https://agentmods.dev/badge/commands/an8079/take-skills/takes-autopilot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.00664 |
| Opus 5 | $0.00013 | $0.00332 |
| Sonnet 5 | $0.00005 | $0.00133 |
| Haiku 4.5 | $0.00003 | $0.00066 |
Grade A, and why
autopilot scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
/autopilot - 全自动执行模式
自主决策执行路径，自动任务分解，持续执行直到完成。
使用方式
/autopilot "任务描述"
或
自动驾驶
自动执行
全自动模式
5 阶段管道
┌────────────────────────────────────────────────────┐
│ 5-Stage Pipeline │
├────────────────────────────────────────────────────┤
│ │
│ ┌───────────┐ ┌───────────┐ ┌───────────┐ │
│ │ Expansion │───▶│ Planning │───▶│ Execution │ │
│ └───────────┘ └───────────┘ └───────────┘ │
│ │ │
│ ┌───────────┴───────────┐ │
│ │ │ │
│ ┌─────▼─────┐ ┌──────▼─────┐
│ │ QA │◀────────│ Validation │
│ └───────────┘ └────────────┘
│ │ │
│ └───────────────────────┘
│ │
│ 目标达成？
│ │
│ ┌─────┴─────┐
│ │ │
│ 退出循环 继续执行
└────────────────────────────────────────────────────┘
阶段说明
| 阶段 | 说明 | 输出 |
|---|---|---|
| Expansion | 扩展任务理解，分析依赖 | 任务图谱 |
| Planning | 制定执行计划，分解任务 | 任务清单 |
| Execution | 执行任务，代码生成 | 产出物 |
| QA | 质量检查，测试验证 | 测试报告 |
| Validation | 验证结果，评估完成度 | 验证结果 |
工作特点
| 特点 | 说明 |
|---|---|
| 自主决策 | 自动决定执行路径 |
| 自动分解 | 将大任务分解为可执行的小任务 |
| 持续执行 | 直到任务验证完成才退出 |
| 自我纠错 | QA 失败时自动回到 Execution |
与 /ralph 的区别
| 维度 | /autopilot | /ralph |
|---|---|---|
| 模式 | 5 阶段管道 | 持久循环 |
| 退出条件 | 验证通过 | Architect 验证通过 |
| 特点 | 自主决策 | 持续迭代 |
提示： /autopilot 是全自动模式，适合明确的任务目标。你只需要描述任务，它会自动完成。
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 81 lines · 26 tokens per session scan A 2b2620151a66
autopilot is a command published in the GitHub repository an8079/take-skills (4 stars, last pushed 5mo ago), licensed MIT. It adds 26 tokens to every session and 664 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.