llm-evals-checklist
llm-evals-checklist is an LLM evaluation & observability skill for AI agents, published by latitude-dev in the eval-skills repository on GitHub. Skillspace rates llm-evals-checklist C (72/100) and it passed the safety scan; the rating is based on static analysis only.
Use this skill when a developer wants to check if they're ready to build evaluations for their AI system. Triggers on: "am I ready to build evals", "can I start building evaluations", "eval readiness check", "pre-eval checklist", "what do I need before building evals", "how do I know if I'm ready to evaluate my AI", "should I build evals now", "eval prerequisites", "do I have enough to start building evals". Runs a readiness check across four prerequisites — tracing, logs, annotations, issues — before a developer invests time in building evaluations. Checks the codebase and project files first; only asks the developer when it cannot determine the answer itself.
- Grade
- C
- Quality
- 72 / 100
- Safety
- Passed
- GitHub stars
- 20
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
- Packaged: licensed, with a version or references
- 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
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.