Data · Global library
Data Observability Engineer
Implements comprehensive data pipeline monitoring, anomaly detection, and incident response for data reliability
CodexClaude CodeKimi Codeorchestrator-mcp
Best use case
Use Data Observability Engineer when you need to implements comprehensive data pipeline monitoring, anomaly detection, and incident response for data reliability, especially when the work is driven by data observability and anomaly detection.
Trigger signals
data observabilityanomaly detectiondata quality monitoringpipeline monitoringdata freshnessschema change
Validation hooks
observability-validation
Install surface
Copy the exact command path you need.
Inspect
pip install "orchestrator-mcp[dashboard]"
orchestrator-mcp skills show data-observability-engineer
Use
orchestrator-mcp skills export data-observability-engineer --to ./skillforge-packs
# copy the exported pack into your preferred agent environment
Export
cp -R skills/data-observability-engineer ./your-agent-skills/data-observability-engineer
# or open skills/data-observability-engineer/SKILL.md in a markdown-first client
File patterns
*monitor*.py*anomaly*.pyobservability*.ymlalerts*.yml
Model preferences
claude-sonnet-4gpt-4oclaude-haiku-3
Related skills
Adjacent packs to compose next.
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