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.
npx agentmods add skills/zjchenqaq/petprompt/optimizenpx skills add zjchenQAQ/petprompt --skill optimizegit clone --depth 1 https://github.com/zjchenQAQ/petpromptWrote 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/skills/zjchenqaq/petprompt/optimize)<a href="https://agentmods.dev/skills/zjchenqaq/petprompt/optimize"><img src="https://agentmods.dev/badge/skills/zjchenqaq/petprompt/optimize.svg" alt="Measured on agentmods" 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 | $0.00055 | $0.00369 |
| Opus 5 | $0.00028 | $0.00185 |
| Sonnet 5 | $0.00011 | $0.00074 |
| Haiku 4.5 | $0.00006 | $0.00037 |
Grade A, and why
optimize 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 5d 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
PetPrompt — optimize a prompt (preview mode)
This is the manual, preview counterpart to PetPrompt's hook. The user wants to SEE a cleaner version of their prompt before running it.
When invoked:
- Take the user's rough request — their arguments if provided, otherwise their most recent message.
- Rewrite it so it follows prompt-engineering best practices: clear, direct, specific, unambiguous, well-structured.
Hard rules — this is a rephrasing, not an expansion:
- Preserve the meaning, intent, and scope EXACTLY.
- Do NOT add new requirements, features, steps, or acceptance criteria the user did not state or clearly imply. Do not pad — the result is usually similar length or shorter.
- Remove hedging, filler, and ambiguity; use precise, imperative phrasing.
- Use the current conversation and project memory (CLAUDE.md) ONLY to resolve ambiguous references (what "it" / "this" points to) and to use correct names/terminology — never to introduce new scope.
- If the prompt is already clear, say so and return it unchanged. Keep the user's language.
Output format:
- Print the rewritten prompt inside a fenced code block so it is easy to copy.
- Follow it with a single-sentence "What changed" note (about phrasing, not added scope).
- Do NOT execute the task. This is preview only — wait for the user to run it.
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.
- 5d ago First seen · 34 lines · 55 tokens per session scan A 9e06fa0e4993
optimize is a skill published in the GitHub repository zjchenQAQ/petprompt (2 stars, last pushed 2mo ago), licensed MIT. It adds 55 tokens to every session and 369 once invoked, about $0.0003 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 skills, from other repositories
prompt-design
Skill "prompt-design" from ryanzhao1011/workframe, covering prompt 设计技能, 适用场景, 五步流程, 第 1 步：场景分析 and 第 2 步：prompt 架构设计.
prompt-evaluation
Prompt 评估与对比，通过维度定义、样本设计、对比测试、量化评分、上线建议的五步流程验证 Prompt 效果.
skill-meta-prompt
Craft better prompts using proven optimization techniques — use when your prompt needs refinement.
ai-workflow-architect
Designs AI systems, automations, and agent workflows for a business — identifying which manual work is worth automating, how to structure the system, which tools fit, and what could go wrong. Use this to automate part of an operation, design an agent or MCP workflow, reduce repetitive manual work, connect tools into a…
cloudflare-workers-ai
Cloudflare Workers AI for serverless GPU inference. Use for LLMs, text/image generation, embeddings, or encountering AIERROR, rate limits, token exceeded errors.
nano-banana-prompting
This skill should be used when crafting prompts for Nano Banana Pro (Gemini image generation). Use when users want help writing image generation prompts, need guidance on prompt structure, or want to optimize their prompts for better results.