About this skill
Identify statistical outliers in warehouse data volume and distribution against learned historical baselines for proactive alerting. Use this skill whenever the user mentions data anomaly, volume anomaly, distribution shift, freshness anomaly, historical baseline, row count spike, schema change alert, or is working with Monte Carlo, dbt, Anomalo, even if they never say \"warehouse statistical anomaly detection\" explicitly. Routes live lookups through the Data-Observability-API endpoint. Do not use it for unrelated application feature work or general coding questions.
Quick start
- Copy the install prompt. Use the green button above this README.
- Send it to your agent. Paste it into your coding agent’s chat and send.
- Review the setup. Your agent checks the skill’s instructions, requirements, and installation scope.
Review, license & listing details
This is an imported listing. We haven’t certified its safety, license, or compatibility. Skills may include executable scripts.
Only SKILL.md was scanned. Supporting files and scripts were not checked. No safety grade has been assigned.
0 potential findings · Scanned 11/4/2026 · Scanner 0.2.1
Content SHA-256: e254f0347be3b552a16cfd5cf210a6ef6b430366b2f3a4c0d52b684df33a7c54
About this listing
- Category
- Science & research
- Reported license
- Not specified
- Listing language (estimated)
- English
- Review status
- Not individually reviewed
- Agent compatibility
- Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.