Agent skill
agent-observability
Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/agent-observability
Metadata
Additional technical details for this skill
- author
- devops-skills
- version
- 1.0
SKILL.md
Agent Observability
Monitor AI agent behavior with logs, traces, metrics, and cost telemetry.
Track Core Signals
- Request latency (p50/p95/p99)
- Token usage (prompt/completion/cached)
- Tool call success and failure rates
- Cost per task and per customer
- Hallucination and retry frequency
Implementation Pattern
- Add trace IDs to every user request.
- Capture each LLM call and tool call as child spans.
- Emit structured logs with model, temperature, and response status.
- Create SLOs for success rate and median response time.
Best Practices
- Redact PII before exporting traces.
- Keep a replayable request envelope for incident review.
- Alert on abnormal token spikes and tool error bursts.
Related Skills
- alerting-oncall - Alert workflows
- agent-evals - Quality verification
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