Telemetry
A ruthlessly strict algorithmic optimization methodology for AI coding agents. Forces your agent to profile, benchmark, and mathematically prove performance gains before writing code.
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Add production observability to a function. Wraps it in an OpenTelemetry or Sentry trace span, injects execution metadata, and proposes a concrete alert rule with threshold and severity.
SKILL.md
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Execute all three phases in order.
Phase 1 — Trace Wrap
Wrap the critical-path function in a trace span:
OpenTelemetry:
tracer.startActiveSpan('operation.name', (span) => {
// ... function body
span.end();
});
Sentry:
const transaction = Sentry.startTransaction({ name: 'operation.name' });
// ... function body
transaction.finish();
Datadog:
tracer.trace('operation.name', () => {
// ... function body
});
Phase 2 — Attribute Injection
Inside the span, attach:
- Execution time (start and stop timer)
- Query tags:
user_id,tenant_id,endpoint - Input and output payload sizes in bytes
Phase 3 — Alert Rule
Propose an alert rule with all four fields specified:
| Field | Value |
|---|---|
| Metric | (e.g. trace.operation.duration) |
| Threshold | (e.g. > 200ms) |
| Evaluation window | (e.g. last 5 minutes) |
| Severity | (e.g. P2 / warning) |
Examples:
- Datadog:
avg(last_5m):avg:trace.operation.duration{env:prod} > 0.200→ P2 - Prometheus:
histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m])) > 0.2→ warning