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/learningmatter-mit/AtomisticSkillsWrote 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/learningmatter-mit/atomisticskills/use-agent-skills)<a href="https://agentmods.dev/rules/learningmatter-mit/atomisticskills/use-agent-skills"><img src="https://agentmods.dev/badge/rules/learningmatter-mit/atomisticskills/use-agent-skills/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/learningmatter-mit/atomisticskills/use-agent-skills"><img src="https://agentmods.dev/badge/rules/learningmatter-mit/atomisticskills/use-agent-skills.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 | $0.00236 | $0.00236 |
| Opus 5.5 | $0.00094 | $0.00094 |
| Sonnet 5.5 | $0.00047 | $0.00047 |
| Haiku 4.5 | $0.00024 | $0.00024 |
Grade A, and why
use-agent-skills scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 21d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Skill Discovery
Use the Grep tool to scan all skill descriptions:
Grep pattern="^description:" glob="skills/*/SKILL.md" output_mode="content"
Instructions
- Run the Grep search above to get all skill descriptions from YAML frontmatter.
- If the user provided a search term ($ARGUMENTS), filter to skills whose name or description matches.
- If no search term was provided, display the full list organized by category prefix:
mat-: Materials scienceml-: Machine learning / MLIPsdrug-: Drug discoverychem-: Chemistry / moleculargeneral-: General utilities
- Present results as a clean table: skill name and description.
- If the user wants to run a skill, read its full
SKILL.mdatskills/<skill-name>/SKILL.mdand follow the numbered instructions step by 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.
- 21d ago Changed · -7 tokens per session 8bbb8d247376
- 1mo ago First seen · 26 lines · 243 tokens per session scan A 3227a8b20f8f
use-agent-skills is a cursor rule published in the GitHub repository learningmatter-mit/AtomisticSkills (186 stars, last pushed yesterday), licensed MIT. It adds 236 tokens to every session, about $0.0009 per session on Opus 5.5. 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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