tune
tune is a Skill evaluation & testing skill for AI agents, published by tkersey in the dotfiles repository on GitHub. Skillspace rates tune C (79/100) and it passed the safety scan; the rating is based on static analysis only.
Tune an existing Codex skill by comparing its intended decision contract with observed decision episodes and outcomes. Prefer `seq skill-decision-audit --mode tune-packet`; use for `$tune`, intended-vs-observed behavior, missed/false/ceremonial activations, ignored clauses, wrong routes, outcome regressions, repeated workarounds, STE-v1 packets, skill-delta candidates, explicit `$refine` handoff, or commit/push authorization for skill-refinement changes. Stop at audit/proposal unless apply or skill-refinement publication is explicit. Commit/push only with explicit publish intent after validation. `$seq` CLI changes require a separate special spec.
- Grade
- C
- Quality
- 79 / 100
- Safety
- Passed
- GitHub stars
- 63
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 97 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- 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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