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Create new skills, modify and improve existing skills, and measure skill performance.
Passed 14 of 20 test cases with the skill, and 5 of 20 without it.
and 14 more in the full report
10 fixed6 passed either way7 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
I'm setting up a skill called 'Executive Sales Summarizer'. Should I name the folder `Executive Sales Summarizer` and put `name: Executive Sales Summarizer` in SKILL.md frontmatter?
| Checked | Without skill | With skill |
|---|---|---|
| Requires the skill folder name to be lowercase and hyphenated like executive-sales-summarizer. | Passed | Passed |
| Requires the frontmatter name field to match the folder name exactly. | Missed | Passed |
The instructions your model reads when the skill loads.
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:
echo "$CHERRY_STUDIO_SKILLS_DIR" in Bash.
That folder is Cherry's managed skill library.$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.Use a lowercase, hyphenated <skill-folder-name> (e.g. my-cool-skill). The name:
field inside your SKILL.md frontmatter must match the folder name and use only
lowercase letters, numbers, and hyphens (e.g. name: my-cool-skill with folder
my-cool-skill), per the Agent Skills spec — it is not a free-form display name.
Eval / test workspaces (<skill-name>-workspace/, iteration-*/, etc.) from the
evaluation loop described below must be created outside that skills directory —
e.g. as a sibling under the user's workspace — so they don't get bundled into the
skill. The evaluation loop itself still applies; only the packaging and install
mechanics change.
A skill for creating new skills and iteratively improving them.
At a high level, the process of creating a skill goes like this:
test cases passed, vs 5 / 20 without
Published skills whose descriptions closely match this one, with their headline benchmark lift.
More skills from the same source and nearby in the registry, with their headline benchmark lift.