Can it help with Big-O complexity issues?

Yes, it provides a before-and-after complexity analysis for every algorithmic solution, ensuring hot paths are optimized for performance.

What kind of 'Bug Debugging Rules' does it follow?

It operates on verification-first principles: reproducing the bug before diagnosis, verifying git logs for changes, and strictly separating debugging from refactoring.

Is it effective for multi-threaded programming?

The skill includes specific procedures for concurrency, helping developers identify shared state and name specific locks to resolve race conditions.

How does this skill improve the debugging process?

It utilizes a structured diagnostic protocol that identifies violated invariants and traces symptoms back to root causes, ensuring the fix is permanent and precise.

Will this skill suggest massive code refactors?

No, it follows a 'surgery, not renovation' philosophy, focusing on the minimal code changes necessary to solve the issue without bloat.

Protocol Core: Algorithmic Surgery

Name: Protocol Core: Algorithmic Surgery
Author: nalyk

bynalyk

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개발자 도구

Resolves complex logic errors and optimizes algorithmic performance through precise, invariant-based debugging and Big-O analysis.

Protocol-Core is a specialized Claude Code skill designed for high-stakes debugging and computational problem-solving. It treats code issues with the precision of a clinical surgery, focusing on isolating root causes through rigorous invariant verification rather than superficial patches. Whether you are battling race conditions, memory leaks, or inefficient nested loops, this skill enforces a strict diagnostic protocol that ensures performance optimizations and bug fixes are both minimal and mathematically sound.

주요 기능

01Invariant-based root cause analysis to trace logic violations

02Detailed Big-O complexity auditing and performance optimization

031 GitHub stars

04Concurrency and race condition isolation through shared state identification

05Minimalist 'surgical' code modifications to reduce regression risks

06Memory leak and recursive logic profiling

사용 사례

01Refactoring an O(n^2) nested loop into a hash-based O(n) lookup for scale.

02Identifying and resolving deadlocks in multi-threaded application logic.

03Debugging non-deterministic logic errors by tracing data state transitions.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nalyk/nalyk-skills-demo protocol-core

For use in Claude.ai and ChatGPT

Download Skill