audit-regret
audit-regret is an Agent security & guardrails skill for AI agents, published by ben-manes in the caffeine repository on GitHub. Skillspace rates audit-regret D (55/100) and it passed the safety scan; the rating is based on static analysis only.
Adversarial workload search for eviction-policy regret. Crafts, shrinks, and classifies workloads on which the adaptive window climber fails to close the gap to its achievable optimum, and routes each failure class to the mechanism responsible (controller, policy structure, or recovery layer)
- Grade
- D
- Quality
- 55 / 100
- Safety
- Passed
- GitHub stars
- 17,865
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
- 84 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- Not declared. Check the repository before reusing it.
What the scanner flagged
- mentions secrets in text
Not checked yet
- Category is a classifier prediction; no model has read this skill 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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