skill-creator
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, 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.
npx skills add CherryHQ/cherry-studio --skill skill-creator --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Cherry Studio workflow (READ FIRST — overrides packaging / install steps below) You are running inside Cherry Studio. Skills live in a managed registry that Cherry keeps in sync with the filesystem automatically — there is **no** install or register tool to call, and you should **ignore** any `package_skill.py` / `.skill` packaging steps mentioned later in this file (they apply to Claude Code / Claude.ai, not here). **To create a new skill, write it straight into Cherry's managed skills directory:** 1. Resolve the directory once by running `echo "$CHERRY_STUDIO_SKILLS_DIR"` in Bash. That folder is Cherry's managed skill library. 2. Create `$CHERRY_STUDIO_SKILLS_DIR/<skill-folder-name>/` and write `SKILL.md` plus any supporting files (`scripts/`, `references/`, `assets/`) into it with your normal file tools. 3. That's it. Cherry's skill sync detects the new directory, registers it in the catalog, and lists it in the app — no register step. You can re-edit the files in place at any time and the changes are picked up on the next sync. Use a lowercase, hyphenated `<skill-folder-name>` (e.g. `my-cool-skill`). The `name:` field inside your `SKILL.md` frontmatter is the display name an
- Cherry Studio workflow (READ FIRST — overrides packaging / install steps below)
- Communicating with the user
- Creating a skill
- Capture Intent
- Interview and Research
- Write the SKILL.md
- Skill Writing Guide
- Writing Style
- Test Cases
- Running and evaluating test cases
- Step 1: Spawn all runs (with-skill AND baseline) in the same turn
- Step 2: While runs are in progress, draft assertions
- Step 3: As runs complete, capture timing data
- Step 4: Grade, aggregate, and launch the viewer
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>
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, edit, 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 CherryHQ/cherry-studio --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 CherryHQ/cherry-studio, a repository with 49,400 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.