empirical-prompt-tuning
empirical-prompt-tuning is a Skill evaluation & testing skill for AI agents, published by yuki-yano in the dotfiles repository on GitHub. Skillspace rates empirical-prompt-tuning D (63/100) and it passed the safety scan; the rating is based on static analysis only.
agent 向けの skill、slash command、AGENTS.md/CLAUDE.md 節、タスクプロンプト、コード生成プロンプトを実証的に改善する。新規作成または大幅改訂した指示の明瞭性、trigger と本文の整合、実行時の不明瞭点、裁量補完、成功率を検証したいときに使う。
- Grade
- D
- Quality
- 63 / 100
- Safety
- Passed
- GitHub stars
- 65
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 91 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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