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python-observability-patterns

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

84

1.17x
Quality

76%

Does it follow best practices?

Impact

100%

1.17x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./data/skills-md/0xdarkmatter/claude-mods/python-observability-patterns/SKILL.md
SKILL.md
Quality
Evals
Security

Evaluation results

100%

4%

Add Distributed Tracing to a Payment Processing Pipeline

OpenTelemetry distributed tracing

Criteria
Without this skill
With this skill

Uses opentelemetry

100%

100%

TracerProvider setup

100%

100%

BatchSpanProcessor

100%

100%

OTLPSpanExporter

100%

100%

OTLP endpoint

100%

100%

set_tracer_provider

100%

100%

get_tracer with __name__

50%

100%

start_as_current_span

100%

100%

span.set_attribute

100%

100%

Nested child spans

100%

100%

Span naming

100%

100%

100%

21%

Add Observability Logging to a User Management Service

Structured logging with structlog

Criteria
Without this skill
With this skill

Uses structlog

100%

100%

merge_contextvars processor

100%

100%

add_log_level processor

50%

100%

TimeStamper ISO format

100%

100%

JSONRenderer processor

100%

100%

wrapper_class setting

50%

100%

PrintLoggerFactory setting

100%

100%

get_logger usage

100%

100%

Keyword-argument log calls

100%

100%

bind_contextvars for request ID

80%

100%

ContextVar for request_id

0%

100%

UUID4 fallback request_id

100%

100%

clear_contextvars after request

50%

100%

100%

18%

Instrument a FastAPI Service with Production Metrics

Prometheus metrics instrumentation

Criteria
Without this skill
With this skill

Uses prometheus_client

100%

100%

Counter for request totals

100%

100%

Histogram for latency

100%

100%

Gauge for active connections

100%

100%

Counter metric name

100%

100%

Histogram metric name

100%

100%

Histogram buckets

0%

100%

Request labels

42%

100%

perf_counter timing

100%

100%

Active connections tracking

100%

100%

/metrics endpoint

100%

100%

generate_latest with text/plain

80%

100%

Repository
NeverSight/learn-skills.dev
Evaluated
Agent
Claude Code
Model
Claude Sonnet 4.6

Table of Contents

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