skills/python/configuring-python-logging/SKILL.md
Choose, configure, or review Python logging for libraries, services, apps, and CLIs, especially when deciding between stdlib logging and Loguru or defining handlers, levels, context, and exception behavior.
npx skillsauth add narumiruna/agent-skills configuring-python-loggingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Choose the logging boundary before choosing syntax.
logging for reusable libraries, long-lived services, mixed ecosystems, and standard Sentry/OpenTelemetry or handler integration.logging.getLogger(__name__); do not configure process-wide handlers or levels during import.references/logging.md for stdlib logger, handler, context, and exception patterns.references/loguru.md only when the application owns Loguru configuration.Do not mix backends without an explicit ownership and interoperability plan, hide global setup in imported modules, or add sinks inside repeatedly called functions.
development
Score or compare one or more agent skills across trigger clarity, workflow actionability, safety boundaries, verification rigor, incremental knowledge value, and leanness. Use only when the user explicitly asks for ratings, numerical quality scores, rubric-based scorecards, or scored comparisons; use creating-agent-skills for unscored reviews or revisions.
development
Assess or improve an existing codebase's architecture when the user asks about module boundaries, coupling, scattered ownership, testability, change locality, deep modules, seams, or behavior-preserving structural refactoring. Use for cross-module design rather than ordinary diff review or a confirmed edge-case bug fix.
development
Perform read-only security audits, vulnerability assessments, or threat-focused reviews of diffs, pull requests, code paths, or explicitly scoped repositories when security is the primary objective or acceptance criterion. Use reviewing-code for ordinary review with baseline security coverage and hardening-code-paths for fixing confirmed findings.
development
Run iterative multi-reviewer panels over a code diff, verify their findings, apply explicitly authorized fixes, and re-review the updated change until it passes or reaches a stopping condition. Use when the user asks for a panel loop, multi-model code-review consensus, or a review-fix-re-review cycle.