Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/magnus919/agent-skillsnpx agentmods add skills/magnus919/agent-skills/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/skills/magnus919/agent-skills/agent-skills)<a href="https://agentmods.dev/skills/magnus919/agent-skills/agent-skills"><img src="https://agentmods.dev/badge/skills/magnus919/agent-skills/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/skills/magnus919/agent-skills/agent-skills"><img src="https://agentmods.dev/badge/skills/magnus919/agent-skills/agent-skills.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00071 | $0.02530 |
| Opus 5 | $0.00036 | $0.01265 |
| Sonnet 5 | $0.00014 | $0.00506 |
| Haiku 4.5 | $0.00007 | $0.00253 |
Grade A, and why
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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Skills Standard Reference
This skill documents the Agent Skills open format — a standardized way to give AI agents new capabilities and expertise. Follow this workflow when creating or editing skills in this repository.
Authoritative source: agentskills.io/specification. The bundled specification is a working snapshot; check the authoritative source when currentness matters.
Directory Structure
A skill is a directory containing, at minimum, a SKILL.md file:
skill-name/
├── SKILL.md # Required: metadata + instructions
├── evals/ # Required for new skills in this repository
├── scripts/ # Optional: executable code
├── references/ # Optional: documentation
├── assets/ # Optional: templates, resources
└── ... # Any additional files or directories
Required Workflow
Create or edit a skill
- Read the specification before changing
SKILL.mdmetadata or directory structure. - Ground instructions in real domain knowledge, project artifacts, and observed failure modes. Read best practices when designing or materially revising instructions.
- Keep the skill a coherent, triggerable unit. Put only essential instructions in
SKILL.md; put conditional detail in focused reference files and state exactly when to read each one. - Use a precise
descriptionthat says what the skill does, when it applies, and when it does not apply. For skills with meaningful overlap, name the nearest alternative or prerequisite in a## When not to usesection. Test the boundary with at least three should-trigger prompts and two should-not-trigger near-misses; keep these harness-specific trigger checks separate from portable output-quality evals. Read optimizing descriptions for trigger design. - For every new skill, create
evals/evals.jsonwith at least five representative output-quality cases. Each case needs a realistic prompt, an expected outcome, and observable assertions. Include edge cases that exercise risky or ambiguous behavior. Read evaluating skills for the eval format and iteration workflow. - When bundling executable code, read using scripts. Document prerequisites and non-interactive invocation in the skill.
- Before handoff, run the validation checks in this skill and correct every finding.
What ships with it
11 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.
- evals/evals.json 9.7 KB
- README.md 2.5 KB
- references/best-practices.md 16 KB
- references/client-implementation.md 20 KB
- references/evaluating-skills.md 17 KB
- references/home.md 23 KB
- references/optimizing-descriptions.md 13 KB
- references/quickstart.md 3.9 KB
- references/specification.md 7.9 KB
- references/using-scripts.md 13 KB
- references/vetting-third-party-skills.md 6.1 KB
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.
- 11d ago First seen · 202 lines · 71 tokens per session scan A fa722681b154
agent-skills is a skill published in the GitHub repository magnus919/agent-skills (76 stars, last pushed today), licensed MIT. It adds 71 tokens to every session and 2,530 once invoked, about $0.0004 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 2026-08-30.
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