Observability setup
AI coding agent runtime that makes LLMs understand your codebase with repository-aware context, memory, and continuous learning
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Define local-first logging, metrics, and diagnostic signals for a runtime surface.
SKILL.md
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Observability Setup
Trigger Signals
- the task needs better local diagnostics or effectiveness tracking
Inspect First
- runtime entrypoints, existing logs, metrics, and failure reporting surfaces
Workflow
- identify the signals worth recording
- choose low-risk local-first storage
- define summary and reporting needs
- recommend the smallest useful setup
Output Contract
- signal inventory
- storage approach
- reporting approach
Failure Modes
- the task lacks a clear runtime boundary to instrument
Escalation
- escalate when observability requirements imply privacy or performance tradeoffs