signals-scout-anomaly-detection
signals-scout-anomaly-detection is a Time series & forecasting skill for AI agents, published by PostHog in the ai-plugin repository on GitHub. Skillspace rates signals-scout-anomaly-detection D (69/100) and it passed the safety scan; the rating is based on static analysis only.
Signals scout that watches a project's most-viewed dashboards and insights for recent anomalies — bursts, drops, flat-lines, and trend breaks scored against each insight's own seasonality-matched baseline. Files each anomaly as a finished 1:1 inbox report on the report channel (emit_report / edit_report) rather than a weak signal.
- Grade
- D
- Quality
- 69 / 100
- Safety
- Passed
- GitHub stars
- 59
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
- 78 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 2 other repositories, in 1 collections
- Scope
- Vendor-specific: built around one product. Watches PostHog dashboards and insights via its public plugin
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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