How-to guide covering the full description optimization workflow:
writing effective descriptions, designing trigger eval queries
(should-trigger and should-not-trigger with near-miss examples), testing
trigger rates with a bash eval script, train/validation splits to avoid
overfitting, and the iterative optimization loop.
The guide is client-agnostic by default but includes a working Claude
Code example in the `check_triggered` function using
`--output-format json` and `jq` to detect `Skill` tool calls.
Adds the page to the "For skill creators" navigation group in
`docs.json`.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Jonathan Hefner