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/huuanh20/awesome-ai-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/rules/huuanh20/awesome-ai-agent-skills/skill-enforcement)<a href="https://agentmods.dev/rules/huuanh20/awesome-ai-agent-skills/skill-enforcement"><img src="https://agentmods.dev/badge/rules/huuanh20/awesome-ai-agent-skills/skill-enforcement/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/rules/huuanh20/awesome-ai-agent-skills/skill-enforcement"><img src="https://agentmods.dev/badge/rules/huuanh20/awesome-ai-agent-skills/skill-enforcement.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 | $0.00168 | $0.00168 |
| Opus 5 | $0.00084 | $0.00084 |
| Sonnet 5 | $0.00034 | $0.00034 |
| Haiku 4.5 | $0.00017 | $0.00017 |
Grade A, and why
skill-enforcement 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 7d 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
Skill Enforcement
- Discover skills under
.cursor/skills/<name>/SKILL.md. - When a skill is selected, read its complete
SKILL.mdbefore acting. - Load referenced files only when the selected skill directs you to them.
- Preserve the order and status of steps in
plans/<slug>/plan.jsonwhen a cook workflow is active. - Do not claim implementation is complete until the required build, test, and review gates for the selected workflow have passed.
- Write handover artifacts to the project directory and reread the latest artifact instead of relying on chat history.
- Ask for direction after three failed remediation cycles on the same plan step.
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.
- 7d ago First seen · 16 lines · 168 tokens per session scan A 182f45559226
skill-enforcement is a cursor rule published in the GitHub repository huuanh20/awesome-ai-agent-skills (1 stars, last pushed 1mo ago), licensed MIT. It adds 168 tokens to every session, about $0.0008 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 2026-09-03.
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