agent-eval-canvas
agent-eval-canvas is an LLM evaluation & observability skill for AI agents, published by GCWing in the BitFun repository on GitHub. Skillspace rates agent-eval-canvas D (59/100) and it passed the safety scan; the rating is based on static analysis only.
Create a BitFun Canvas for single-case agent evaluation and trajectory diagnosis. Use when the user asks to analyze one agent run, trace, case, benchmark item, failure trajectory, eval result, or critical failure step, and wants an incident-review style report covering verdict, step timeline, root cause, error propagation, tool/evidence analysis, efficiency, safety, and repair recommendations.
- Grade
- D
- Quality
- 59 / 100
- Safety
- Passed
- GitHub stars
- 1,333
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
- 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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