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 psenger/ai-agent-skills --skill create-a-skillgit clone --depth 1 https://github.com/psenger/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/skills/psenger/ai-agent-skills/create-a-skill)<a href="https://agentmods.dev/skills/psenger/ai-agent-skills/create-a-skill"><img src="https://agentmods.dev/badge/skills/psenger/ai-agent-skills/create-a-skill/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/psenger/ai-agent-skills/create-a-skill"><img src="https://agentmods.dev/badge/skills/psenger/ai-agent-skills/create-a-skill.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 | $0.00115 | $0.04046 |
| Opus 5 | $0.00057 | $0.02023 |
| Sonnet 5 | $0.00023 | $0.00809 |
| Haiku 4.5 | $0.00012 | $0.00405 |
Grade A, and why
create-a-skill 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.
How it starts
The opening of the file, as written. The whole thing — 467 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create a Skill
A skill for creating new skills from scratch and iteratively improving them through testing, user feedback, and evaluation.
Overview
The process of creating a skill follows this loop:
- Gather requirements — interview the user, research the domain
- Write a draft — create SKILL.md and any bundled resources
- Test — run Claude-with-the-skill on realistic prompts
- Evaluate — help the user review outputs qualitatively and quantitatively
- Improve — rewrite based on feedback
- Repeat until the user is satisfied
- Optimize description — tune triggering accuracy
- Package — create a distributable
.skillfile
Your job is to figure out where the user is in this process and jump in. Maybe they say "I want to make a skill for X" — help them from step 1. Maybe they already have a draft — go straight to testing. Always be flexible: if the user says "just vibe with me", skip the formal eval loop.
Phase 1: Gather Requirements
Capture Intent
Start by understanding what the user wants. The conversation might already contain a workflow they want to capture (e.g., "turn this into a skill"). If so, extract answers from the conversation history first — tools used, sequence of steps, corrections the user made, input/output formats observed.
Ask these questions (skip any already answered):
- What should this skill enable Claude to do? — the core capability
- What task or domain does it cover? — scope and boundaries
- What specific use cases should it handle? — concrete scenarios
- When should this skill trigger? — user phrases, contexts, keywords
- What's the expected output format? — files, text, structured data
- Does it need executable scripts or just instructions? — deterministic operations
- Any reference materials to include? — docs, APIs, schemas
- Should we set up test cases? — skills with objectively verifiable outputs (file transforms, data extraction, code generation) benefit from test cases; subjective skills (writing style, art) often don't. Suggest the appropriate default, but let the user decide.
What ships with it
19 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.
- agents/analyzer.md 10 KB
- agents/comparator.md 7.1 KB
- agents/grader.md 8.8 KB
- assets/eval_review.html 6.9 KB
- eval-viewer/generate_review.py 16 KB runs code
- eval-viewer/viewer.html 44 KB
- LICENSE.txt 11 KB
- NOTICE 399 B
- README.md 5.3 KB
- references/schemas.md 12 KB
- scripts/__init__.py 0 B runs code
- scripts/aggregate_benchmark.py 14 KB runs code
- scripts/generate_report.py 13 KB runs code
- scripts/improve_description.py 11 KB runs code
- scripts/package_skill.py 4.1 KB runs code
- scripts/quick_validate.py 3.9 KB runs code
- scripts/run_eval.py 11 KB runs code
- scripts/run_loop.py 14 KB runs code
- scripts/utils.py 1.6 KB runs code
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 · 467 lines · 115 tokens per session scan A fcd86a192fd6
create-a-skill is a skill published in the GitHub repository psenger/ai-agent-skills (10 stars, last pushed 3mo ago), licensed MIT. It adds 115 tokens to every session and 4,046 once invoked, about $0.0006 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.
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