skill-creator
Creates new skills, improves existing ones, runs evals and benchmarks skill performance.
- Kind
- Skill
- Works with
- Claude Code
- Source
- anthropics/claude-plugins-official @ 58267944f921
- Path
- plugins/skill-creator/skills/skill-creator/SKILL.md
- Jobs
- Implementation, Testing
- Topics
- LLM apps & RAG, Agents & MCP
Credit
- Made by
- anthropics
- Original
- github.com/anthropics/claude-plugins-official/blob/58267944f9…
- License
- Apache-2.0
Listed by Skill Manifest; not made by us.
InstallInstall it from a plugin marketplace.
/plugin install skill-creator@claude-plugins-official
Install factsScanned 2 Nov 2026
- Adds
- .claude/skills/skill-creator/ (the skill folder)
- 2 file(s) the skill refers to
- Runs scripts
- Yes
- shell block in the text
- Uses the network
- None found
- Needs secrets
- None found
- Reads environment variables
- VIEWER_PID
- Source revision
- 58267944f921
- Licence
- Apache-2.0
- Last activity
- 1 Nov 2026
- Review
- Reviewed
Found by a static scan of the stored text; nothing is run. “None found” is not a guarantee, so read what you install before you run it.
- Only the main file is read; other files in the folder are not scanned
# 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 …