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/TestAny-io/testany-agent-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/testany-io/testany-agent-skills/prompt-optimizer)<a href="https://agentmods.dev/commands/testany-io/testany-agent-skills/prompt-optimizer"><img src="https://agentmods.dev/badge/commands/testany-io/testany-agent-skills/prompt-optimizer/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/testany-io/testany-agent-skills/prompt-optimizer"><img src="https://agentmods.dev/badge/commands/testany-io/testany-agent-skills/prompt-optimizer.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 | $0.00009 | $0.00287 |
| Opus 5 | $0.00005 | $0.00143 |
| Sonnet 5 | $0.00002 | $0.00057 |
| Haiku 4.5 | $0.00001 | $0.00029 |
Grade A, and why
prompt-optimizer 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 3d 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
Prompt Optimizer
启动提示词优化流程。将模糊的想法转化为精确有效的 AI 提示词。
在 Claude Code 中，skill 会在停止前自动做一次质量复核，避免过早交付。
使用方式
提供你的原始提示词或需求描述：
$ARGUMENTS
支持的平台
- Claude - XML 标签结构
- ChatGPT - Markdown 结构
- DeepSeek - CoT 友好格式
- 豆包 - 简洁中文风格
- 智谱 GLM - 结构化中文
- Gemini - 清晰指令格式
优化方法论（4D）
- Define - 明确意图和目标
- Decompose - 拆解复杂任务
- Demonstrate - 添加示例
- Debug - 迭代优化
自我评判清单
- 意图清晰
- 无歧义
- 信息完整
- 结构合理
- 平台适配
- 精简度
- 可执行
请提供你的原始提示词开始优化。
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.
- 3d ago First seen · 45 lines · 9 tokens per session scan A d7a31355acaa
prompt-optimizer is a command published in the GitHub repository TestAny-io/testany-agent-skills (82 stars, last pushed 4d ago), licensed MIT. It adds 9 tokens to every session and 287 once invoked, about $0.0000 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 2026-09-08.
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.