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-po)<a href="https://agentmods.dev/commands/an8079/take-skills/takes-po"><img src="https://agentmods.dev/badge/commands/an8079/take-skills/takes-po/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-po"><img src="https://agentmods.dev/badge/commands/an8079/take-skills/takes-po.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 | $0.00035 | $0.00686 |
| Opus 5 | $0.00017 | $0.00343 |
| Sonnet 5 | $0.00007 | $0.00137 |
| Haiku 4.5 | $0.00003 | $0.00069 |
Grade A, and why
takes-po 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
📝 /takes-po — Prompt Optimizer
将用户的自然语言需求转化为结构化、高效的提示词。
核心框架
## 角色 (Role)
你是一个[专业身份]，擅长...
## 背景 (Context)
[项目的背景信息、现有情况、约束条件]
## 任务 (Task)
请帮我完成[具体任务描述]
## 要求 (Requirements)
- [硬性要求/必须满足的条件]
- [输出格式要求]
- [质量标准]
## 参考 (References)
[如果有的话，提供相关文件、代码、示例]
## 输出格式 (Output Format)
[期望的输出结构，如：代码块、文档结构、步骤列表等]
优化规则
- 角色明确 — 给 AI 分配一个专业身份
- 目标具体 — 说明最终要什么，不是过程
- 边界清晰 — 列出约束条件和范围
- 示例辅助 — 提供参考样式或反例
- 格式指定 — 明确输出结构
触发方式
/takes-po # 激活优化模式
/takes-po [自然语言需求] # 直接优化需求
帮我优化提示词 # 自然语言触发
优化一下这个需求 # 自然语言触发
使用场景
| 场景 | 示例 |
|---|---|
| 需求模糊 | "帮我写个项目" → 结构化项目需求 |
| 提示词优化 | "帮我写个代码" → "你是一个资深 React 工程师..." |
| 学习提升 | 展示优化过程，学习如何写好提示词 |
输出示例
用户输入：
帮我写个博客网站
优化输出：
## 角色 (Role)
你是一个资深全栈工程师，擅长 Next.js、TypeScript 和现代前端架构。
## 背景 (Context)
用户需要一个技术博客网站，用于分享技术文章。
已有域名，部署在 Vercel 上。
## 任务 (Task)
请帮我完成一个技术博客网站的开发。
## 要求 (Requirements)
- 使用 Next.js 14 App Router
- TypeScript 严格模式
- 支持 Markdown 文章
- 有文章分类和标签功能
- 响应式设计，适配移动端
- SEO 友好，支持 OG tags
## 输出格式 (Output Format)
- 项目结构说明
- 核心代码文件
- 部署步骤
<!-- Original: 帮我写个博客网站 -->
提示： /takes-po 不仅优化需求，还教你怎么写更好的提示词。
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 · 100 lines · 35 tokens per session scan A 41e79359ec57
takes-po is a command published in the GitHub repository an8079/take-skills (4 stars, last pushed 5mo ago), licensed MIT. It adds 35 tokens to every session and 686 once invoked, about $0.0002 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
prompt
System instructions for writing effective prompts. Apply when generating commands, skills, agents, or any LLM instructions.
prompt-show
Display full details of a saved prompt by ID.
music-suno-prompt
Grounded Suno prompt synthesis from local knowledge corpus + persona canon + label canon. No vibes-prompting.
ai
Load the Kaizen skill for production-ready AI agent implementation with signature-based programming and multi-agent coordination.
audit-prompt
Evaluate an existing prompt for clarity, effectiveness, and edge cases.
develop-image-prompt.eval
Generates a detailed image generation prompt from a document or content description. Good output: a prompt that is specific, visual, non-abstract, includes style/composition/lighting guidance, and is calibrated to the specified dimensions and style options.