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diagnose

Diagnose software bugs and performance issues through a structured debugging loop.

Updated May 15, 2026
Search Tags:#code analysis#debugging#software development#performance analysis#bug diagnosis
One-click install
npx skills add https://github.com/ruskibeats/t1d --skill diagnose-ruskibeats
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: diagnose
Source: https://github.com/ruskibeats/t1d/tree/main/.agents/skills-archive/engineering/diagnose
Command: npx skills add https://github.com/ruskibeats/t1d --skill diagnose-ruskibeats

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill provides a systematic approach to diagnose complex bugs and performance regressions in software development.

Core Features & Use Cases

  • Structured Bug Diagnosis: Follows a disciplined loop for bug diagnosis (Reproduce → Minimise → Hypothesise → Instrument → Fix → Regression-test).
  • Multi-Method Feedback Loops: Offers various methods to construct feedback loops for reproducibility, including failing tests, scripts, and manual checks.
  • Instrumentation and Analysis: Provides guidelines for effective instrumentation and analysis during the debugging process.
  • Regression Testing: Ensures that fixes are thoroughly tested to prevent regressions.

Quick Start

Run the diagnose skill to initiate the bug diagnosis process and follow the structured loop.

Frequently Asked Questions about diagnose

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is the best way to diagnose hard-to-find software bugs systematically?▼

Systematic bug diagnosis follows a structured loop: reproduce, minimise, hypothesise, instrument, fix, and regression-test. This disciplined approach isolates root causes for complex software issues and performance regressions rather than relying on trial and error.

How do I build feedback loops for reproducing software bugs during debugging?▼

Build feedback loops for bug reproduction using failing tests, dedicated scripts, or manual checks. These methods establish reliable reproducibility, which is essential for accurately verifying hypotheses and instrumenting code during the debugging process.

What steps are involved in instrumenting code for performance analysis and bug diagnosis?▼

Instrumenting code for performance analysis involves adding targeted telemetry to verify hypothesised causes. After reproducing and minimising the bug, you instrument the specific code paths to capture data, apply a fix, and then execute regression testing.

Do I need Python to use this structured debugging and code analysis process?▼

Yes, you need Python installed in your environment to execute the scripts required by this bug diagnosis process. Familiarity with standard debugging and code analysis techniques is also assumed to effectively follow the structured loop.

How does a structured bug diagnosis process compare to standard debugging workflows?▼

A structured bug diagnosis process enforces a strict sequence—reproduce, minimise, hypothesise, instrument, fix, regression-test—unlike ad-hoc debugging. This methodical loop ensures thorough instrumentation and prevents regressions, yielding more reliable software fixes.

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