python-observability-patterns

Observability patterns for Python applications. Triggers on: logging, metrics, tracing, opentelemetry, prometheus, observability, monitoring, structlog, correlation id.

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Review — 80%

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Validation — 10 / 11 Passed

Validation for skill structure

SKILL.md

Review

Evals

Evaluation results

100%

21%

Add Observability Logging to a User Management Service

Structured logging with structlog

Criteria

Without context

With context

Uses structlog

100%

merge_contextvars processor

100%

add_log_level processor

50%

100%

TimeStamper ISO format

100%

JSONRenderer processor

100%

wrapper_class setting

50%

100%

PrintLoggerFactory setting

100%

get_logger usage

100%

Keyword-argument log calls

100%

bind_contextvars for request ID

80%

100%

ContextVar for request_id

100%

UUID4 fallback request_id

100%

clear_contextvars after request

50%

100%

Without context: $0.2826 · 1m 7s · 16 turns · 23 in / 4,127 out tokens

With context: $0.5085 · 1m 27s · 28 turns · 33 in / 4,903 out tokens

100%

18%

Instrument a FastAPI Service with Production Metrics

Prometheus metrics instrumentation

Criteria

Without context

With context

Uses prometheus_client

100%

Counter for request totals

100%

Histogram for latency

100%

Gauge for active connections

100%

Counter metric name

100%

Histogram metric name

100%

Histogram buckets

100%

Request labels

42%

100%

perf_counter timing

100%

Active connections tracking

100%

/metrics endpoint

100%

generate_latest with text/plain

80%

100%

Without context: $0.2918 · 1m 7s · 20 turns · 23 in / 4,029 out tokens

With context: $0.3108 · 55s · 17 turns · 272 in / 3,300 out tokens

100%

Add Distributed Tracing to a Payment Processing Pipeline

OpenTelemetry distributed tracing

Criteria

Without context

With context

Uses opentelemetry

100%

TracerProvider setup

100%

BatchSpanProcessor

100%

OTLPSpanExporter

100%

OTLP endpoint

100%

set_tracer_provider

100%

get_tracer with __name__

50%

100%

start_as_current_span

100%

span.set_attribute

100%

Nested child spans

100%

Span naming

100%

Without context: $0.1948 · 41s · 11 turns · 13 in / 2,992 out tokens

With context: $0.4903 · 1m 40s · 25 turns · 388 in / 5,842 out tokens

Evaluated: about 13 hours ago
Agent: Claude Code

Table of Contents

Add Observability Logging to a User Management Service Instrument a FastAPI Service with Production Metrics Add Distributed Tracing to a Payment Processing Pipeline

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