agent-eval
agent-eval is an LLM evaluation & observability skill for AI agents, published by affaan-m in the ECC repository on GitHub. Skillspace rates agent-eval C (74/100) and it passed the safety scan; a judge model has also reviewed it.
Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.
- Grade
- C
- Quality
- 74 / 100
- Safety
- Passed
- GitHub stars
- 255,679
Placed #2 of 6 in the judged category final for LLM evaluation & observability.
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
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Judge review
Placed #2 of 6 in the judged category final for LLM evaluation & observability.
- Trigger
85 85 - Instructions
85 85 - Specificity
88 88 - Safety
85 85 - Disclosure
75 75 - Maintenance
80 80
Reproducible YAML task definitions, worktree isolation, and explicit variance and cost-aware best practices make this a genuinely rigorous comparison harness.
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- 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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