detect-anomalies
detect-anomalies is an Observability & incident response skill for AI agents, published by axiomhq in the cli repository on GitHub. Skillspace rates detect-anomalies D (64/100) and it passed the safety scan; the rating is based on static analysis only.
Detect anomalies in Axiom datasets using statistical analysis. Use when looking for unusual patterns, volume spikes, outliers, or new error types in observability data.
- Grade
- D
- Quality
- 64 / 100
- Safety
- Passed
- GitHub stars
- 58
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
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- over-broad allowed-tools ('*')
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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