How does it track logs across different functions?

It implements a correlation ID system using context propagation (such as contextvars or request state) to link logs from the initial entry point down to the deepest internal calls.

Does this add significant overhead to my application?

No, the skill prioritizes 'cheap' logging by utilizing monotonic clocks and avoiding heavy formatting or blocking operations unless the specific log level is enabled.

Can I customize the warning thresholds for slow code?

Yes, the implementation pattern includes a 'warn_ms' parameter that allows you to define thresholds and automatically highlight spans that exceed your performance targets.

What languages does this skill support?

While the logic and patterns are universal, the skill provides specific implementation guidance for Python and web-based backend environments using monotonic clocks like perf_counter.

Human-Readable Latency Logging

Name: Human-Readable Latency Logging
Author: bakwankawa

bybakwankawa

0•

分析と監視

Instruments code with structured, timestamped logs and per-function timing breakdowns to pinpoint performance bottlenecks.

This skill empowers Claude to implement high-quality observability patterns by adding human-readable logs and detailed latency breakdowns. It automates the creation of structured spans, correlation IDs, and nested timing logs using monotonic clocks, making it easy to identify exactly where an application is slowing down. It is particularly useful for profiling API routes, database queries, and external dependency calls without cluttering the codebase with noisy, unstructured print statements, ensuring that performance insights are both readable and actionable.

主な機能

01Human-readable local timestamps and nested sub-span indentation

020 GitHub stars

03Detailed per-function timing breakdowns with aligned duration outputs

04Configurable warning thresholds to highlight slow operations automatically

05Performance-first implementation using monotonic clocks for high precision

06Automatic correlation ID generation for request-scoped log tracking

ユースケース

01Profiling API request flows to find slow database queries or external service calls

02Debugging intermittent latency spikes in complex, nested function calls

03Adding structured observability to existing microservices or backend applications

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add bakwankawa/lazy-code-skill lazy-code-skill

For use in Claude.ai and ChatGPT

Download Skill