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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.