error-discovery
error-discovery is an LLM evaluation & observability skill for AI agents, published by shreyashankar in the error-discovery-skill repository on GitHub. Skillspace rates error-discovery D (62/100) and it passed the safety scan; the rating is based on static analysis only.
Run error analysis on a dataset. Build a review UI, select diverse samples, monitor annotations, and organize failure modes.
- Grade
- D
- Quality
- 62 / 100
- Safety
- Passed
- GitHub stars
- 586
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
- 89 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
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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