Agent skill · Testing & QA

skill-creator

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-codeships scripts
Install
npx skills add ECNU-ICALK/AutoSkill --skill skill-creator --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 18
SKILL.md size: 31 KB
Bundled scripts: yes
Path: SkillBank/Common/anthropics-skill/skill-creator/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 539
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

Review
written from the skill's own SKILL.md · Aug 5, 2026

What it does

Aimed at creating new skills and iteratively improving them. It helps determine user intent, drafts a skill, creates test prompts, runs evaluations using claude-with-access-to-the-skill, and assists in evaluating results both qualitatively and quantitatively. It suggests rewriting the skill based on user feedback and benchmarks, expands test sets, and can optimize the triggering description after the skill is completed. It supports guiding the user through discovery, drafting, evaluation, and iteration, or jumping straight to evaluation if a draft exists.

How it works

  • 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 claude-with-access-to-the-skill on them.
  • Help the user evaluate results qualitatively and quantitatively.
    • While runs occur in the background, draft quantitative evals if none exist, or adjust existing ones.
    • Use the eval-viewer/generate_review.py script to show results and metrics to the user.
  • Rewrite the skill based on feedback and obvious flaws from benchmarks.
  • Repeat until satisfactory, then expand the test set and re-run at larger scale.
  • Optionally run the skill description improver to optimize triggering accuracy.

When to use it

Use when a user wants to create a skill from scratch, update or optimize an existing skill, run evaluations to test a skill, benchmark skill performance with variance analysis, or optimize the skill's description for triggering accuracy.

What it can touch

  • Tools: claude-code is declared as a tool.
  • Scripts: it references eval-viewer/generate_review.py for displaying results and evals.json for test prompts and benchmarks.

Caveats

  • Focuses on iterative, measurable evaluation and improvement cycles.
  • Excludes any guarantees about outcomes; results depend on user-provided prompts, test cases, and evaluation criteria.
  • Descriptions and triggering optimization should be grounded in user feedback and objective metrics as outlined in the workflow.
From the SKILL.md

# 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 you want the skill to do and roughly how it should do it - Write a draft of the skill - Create a few test prompts and run claude-with-access-to-the-skill on them - Help the user evaluate the results both qualitatively and quantitatively - While the runs happen in the background, draft some quantitative evals if there aren't any (if there are some, you can either use as is or modify if you feel something needs to change about them). Then explain them to the user (or if they already existed, explain the ones that already exist) - Use the `eval-viewer/generate_review.py` script to show the user the results for them to look at, and also let them look at the quantitative metrics - Rewrite the skill based on feedback from the user's evaluation of the results (and also if there are any glaring flaws that become apparent from the quantitative benchmarks) - Repeat until you're satisfied - Expand the test set and try again at larger scale Your job when using this skill is to figure out where the user is in this process and then jump in

What's inside
Steps it walks through
  1. Communicating with the user
  2. Creating a skill
  3. Capture Intent
  4. Interview and Research
  5. Write the SKILL.md
  6. Skill Writing Guide
  7. Writing Style
  8. Test Cases
  9. Running and evaluating test cases
  10. Step 1: Spawn all runs (with-skill AND baseline) in the same turn
  11. Step 2: While runs are in progress, draft assertions
  12. Step 3: As runs complete, capture timing data
  13. Step 4: Grade, aggregate, and launch the viewer
  14. What the user sees in the viewer
Ships with 17 files
  • LICENSE.txt
  • agents/analyzer.md
  • agents/comparator.md
  • agents/grader.md
  • assets/eval_review.html
  • eval-viewer/generate_review.py
  • eval-viewer/viewer.html
  • references/schemas.md
  • scripts/__init__.py
  • scripts/aggregate_benchmark.py
  • scripts/generate_report.py
  • scripts/improve_description.py
  • scripts/package_skill.py
  • scripts/quick_validate.py
  • scripts/run_eval.py
  • scripts/run_loop.py
  • scripts/utils.py
Commands it runs
python -m scripts.aggregate_benchmark <workspace>/iteration-N --skill-name <name>
nohup python <skill-creator-path>/eval-viewer/generate_review.py \
kill $VIEWER_PID 2>/dev/null
python -m scripts.run_loop \
python -m scripts.package_skill <path/to/skill-folder>
More from AutoSkill
All skills →
About this skill
What does the skill-creator skill do?

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill skill-creator --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going