| name | telemetry-analytics |
| description | Design telemetry and analytics systems for reliable KPI tracking and decision support. Use when defining event schemas, metric derivations, analytics pipelines, anomaly checks, or validating telemetry coverage for product releases. |
Telemetry Analytics
Use this skill to define telemetry pipelines and analytics outputs with KPI trustworthiness.
Workflow
- Define scope and constraints.
- Define KPI questions, event taxonomy, and data quality constraints.
- Capture objective metrics, bounds, and release blockers.
- Design implementation plan.
- Design ingestion, transformation, and aggregation flow with lineage.
- Keep ownership and dependency boundaries explicit.
- Execute and iterate.
- Implement in small, traceable increments.
- Record run/build context for reproducibility.
- Validate contract integrity.
- Validate event completeness, metric accuracy, and anomaly detection gates.
- Treat contract breaches as blockers.
- Prepare handoff.
- Deliver schema updates, dashboard mapping, and quality checks.
- Include exact commands and acceptance criteria.
Output Contract
Return:
Context: goals, assumptions, constraints.Validation: pass/fail checks and key deltas.Changes: concrete file-level updates.Commands: commands and expected outputs.Risks: unresolved issues and limits.
References
references/workflow.md: detailed execution flow.references/checklist.md: sign-off checklist.
Execution Rules
- Keep decisions measurable and reversible.
- Keep validation criteria explicit before iteration.
- Flag missing instrumentation and unverifiable KPI derivations as blockers.
