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 Zhang-Henry/CoEvoSkills --skill skill-creatorgit clone --depth 1 https://github.com/Zhang-Henry/CoEvoSkillsWrote 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/zhang-henry/coevoskills/skill-creator)<a href="https://agentmods.dev/skills/zhang-henry/coevoskills/skill-creator"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/skill-creator/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/zhang-henry/coevoskills/skill-creator"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/skill-creator.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 | $0.00064 | $0.02025 |
| Opus 5 | $0.00032 | $0.01012 |
| Sonnet 5 | $0.00013 | $0.00405 |
| Haiku 4.5 | $0.00006 | $0.00202 |
Grade A, and why
skill-creator 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 6d 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 — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Creator
A skill for creating new skills and iteratively improving them.
At a high level, the process of creating a skill goes like this:
- Decide what the skill should do and roughly how it should do it
- Write a draft of the skill
- Create a few test prompts and run them with the skill (spawn subagents)
- Evaluate the results both qualitatively and quantitatively
- Draft quantitative assertions and grade the outputs
- Compare with-skill vs baseline (without-skill) results
- Rewrite the skill based on what went wrong
- Repeat until the skill consistently improves outputs over baseline
- Expand the test set and try again at larger scale
This is a fully autonomous workflow — make all decisions yourself, do not wait for or request human feedback at any step. Proceed through the full draft → test → grade → improve → retest loop without stopping.
Creating a skill
Capture Intent
Analyze the task description to determine:
- What should this skill enable Claude to do?
- When should this skill trigger? (what contexts)
- What's the expected output format?
- What are the key domain constraints and edge cases?
Research
Examine the input files, data formats, and any domain-specific requirements. Understand the task deeply before writing the skill.
Write the SKILL.md
Fill in these components:
- name: Skill identifier
- description: When to trigger, what it does. This is the primary triggering mechanism - include both what the skill does AND specific contexts for when to use it. Make descriptions comprehensive — include all relevant use cases.
- compatibility: Required tools, dependencies (optional, rarely needed)
- the rest of the skill
Skill Writing Guide
Anatomy of a Skill
skill-name/
├── SKILL.md (required)
│ ├── YAML frontmatter (name, description required)
│ └── Markdown instructions
└── Bundled Resources (optional)
├── scripts/ - Executable code for deterministic/repetitive tasks
├── references/ - Docs loaded into context as needed
└── assets/ - Files used in output (templates, icons, fonts)
What ships with it
17 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
- 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 4.5 KB runs code
- scripts/run_eval.py 11 KB runs code
- scripts/run_loop.py 13 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.
- 6d ago First seen · 252 lines · 64 tokens per session scan A 6588e4080dda
skill-creator is a skill published in the GitHub repository Zhang-Henry/CoEvoSkills (66 stars, last pushed 20d ago), licensed Apache-2.0. It adds 64 tokens to every session and 2,025 once invoked, about $0.0003 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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