Logging

Logging

This skill is self-contained for day-to-day use. Deeper reference (needs the full harness checkout): patterns/logging/LOGGING_STANDARDS.md (full mandate and config schema), patterns/logging/logging.yaml.example (tested YAML template), patterns/logging/config_loader.py (Python reference implementation with 99% test coverage).

When this applies

Full structured logging with YAML config, multiple backends, and rotation is required at Production tier. Prototypes: print()/console.log() is fine. Internal tools: structured logging recommended, single-backend acceptable. Check the project's rigor tier first.

Log levels — pick the right one

Rule of thumb: if you'd page someone at 3am, it's ERROR or CRITICAL.

Structured logging: message + fields, never string interpolation

# WRONG: unstructured — can't query or filter by user_id or duration
logger.info(f"Request completed for user {user_id} in {duration}ms")

# RIGHT: message is a static label; context is in structured fields
logger.info("request.completed", user_id=user_id, duration_ms=duration)

// Node/pino/winston equivalent
logger.info({ userId, durationMs }, 'request.completed');

What NOT to log

Never log: passwords, tokens, API keys, full credit card numbers, SSNs, session IDs, or any data under a PII/GDPR policy. Redact or omit before logging. If logging usefulness and secrecy conflict, redact. Do not log the secret "for completeness."

# WRONG: logs the raw token
logger.info("auth.token_issued", token=issued_token)

# RIGHT: log only what's safe to expose
logger.info("auth.token_issued", user_id=user_id, expires_at=exp)

Configuration: YAML template, not hand-rolled

Copy patterns/logging/logging.yaml.example as your starting point:

cp patterns/logging/logging.yaml.example config/logging.yaml

The template supports ${VAR:-default} interpolation, multiple handler backends (file, console, OTEL), and rotation. Hand-rolling a logging schema from scratch duplicates tested work.

Verification before marking work complete

1. Run the code path and confirm log lines actually emit — don't assume.
2. Pipe a log line through jq (or equivalent) to confirm it's valid JSON (or whatever your configured format is).
3. State in the PR description which events you verified emit correctly.

Local vs. production output

Local/dev: human-readable (pretty / dev format, colorized). Production: machine-parseable JSON, no color codes. Configure this via an environment variable, not a code branch:

handlers:
  console:
    formatter: ${LOG_FORMAT:-json}   # override to 'pretty' in dev