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 skills add tranfu-labs/tranfu-skills --skill skill-reverse-engineergit clone --depth 1 https://github.com/tranfu-labs/tranfu-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/skills/tranfu-labs/tranfu-skills/skill-reverse-engineer)<a href="https://agentmods.dev/skills/tranfu-labs/tranfu-skills/skill-reverse-engineer"><img src="https://agentmods.dev/badge/skills/tranfu-labs/tranfu-skills/skill-reverse-engineer/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/skills/tranfu-labs/tranfu-skills/skill-reverse-engineer"><img src="https://agentmods.dev/badge/skills/tranfu-labs/tranfu-skills/skill-reverse-engineer.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 | $0.00036 | $0.02332 |
| Opus 5 | $0.00018 | $0.01166 |
| Sonnet 5 | $0.00007 | $0.00466 |
| Haiku 4.5 | $0.00004 | $0.00233 |
Grade A, and why
skill-reverse-engineer 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 9d 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.
This is a copy
94% identical to skill-reverse-engineer — 16 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 305 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Reverse Engineer
Overview
Reverse-engineer visible AI Agent Skills, SKILL.md files, prompt workflows, agent instruction packages, marketplace pages, or skill directories.
Treat the artifact as a designed system, not just text. Identify its intent, trigger logic, workflow, resource strategy, quality level, risks, tests, and reusable creation formula.
Always separate visible evidence from inference. Never claim access to hidden system prompts, private platform routing, marketplace ranking logic, or unavailable files.
Use the lightest output that satisfies the user. A concise diagnosis is better than a full report when the user only asks for a quick read.
同类 Skill 对比
暂无。
使用技巧
暂无（作者跳过）。
Mode Selection
Choose one mode before analyzing:
| Mode | Use when | Output |
|---|---|---|
| Quick diagnosis | The user asks what the skill is, whether it is good, or why it works | Core judgment, trigger logic, workflow, top risks |
| Full reverse engineering | The user asks how the skill was built or asks for a full analysis | Structural report, pattern extraction, creation formula |
| Improvement audit | The user asks to improve, rewrite, or strengthen the skill | Defects, rationale, targeted rewrite or full SKILL.md |
| Trigger test | The user asks whether the skill will activate reliably | Should-trigger, should-not-trigger, ambiguous, and edge queries |
| Marketplace package | The user asks to publish or package the skill | Positioning, folder structure, SKILL.md, tests, release checklist |
| Comparison | The user provides multiple skills | Shared formula, differences, reusable template |
If the user does not specify a mode, infer it from the request. Prefer quick diagnosis for exploratory questions and improvement audit for rewrite requests.
Inputs
The user may provide:
- Full
SKILL.mdcontent. - A skill directory tree.
- A marketplace skill page.
- A prompt workflow or agent instruction package.
- Supporting files such as scripts, references, assets, examples, tests, templates, or metadata.
- Multiple skills for comparison.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 305 lines · 36 tokens per session scan A 3a21081c32c0
skill-reverse-engineer is a skill published in the GitHub repository tranfu-labs/tranfu-skills (2 stars, last pushed 2d ago), licensed MIT. It adds 36 tokens to every session and 2,332 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to skill-reverse-engineer, differing in 16 lines, and is treated as a copy.
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