Evals
Evals is an LLM evaluation & observability skill for AI agents, published by danielmiessler in the LifeOS repository on GitHub. Skillspace rates Evals B (80/100) and it passed the safety scan; the rating is based on static analysis only.
AI agent evaluation framework with three grader types (code-based, model-based, human) and pass@k/pass^k scoring over agent transcripts, tool-call sequences, and multi-turn conversations; covers capability and regression evals. USE WHEN eval, evaluate, benchmark, regression test, compare models, create judge, test agent, pass@k, scenario simulation. NOT FOR scientific method framing (use Science).
- Grade
- B
- Quality
- 80 / 100
- Safety
- Passed
- GitHub stars
- 16,717
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
- 94 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Portable: works in any project. General agent eval framework; LifeOS customizations optional
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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