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diagnose

Convert bug symptoms into a deterministic pass/fail feedback loop.

1|Updated May 5, 2026
Search Tags:#debugging#instrumentation#regression testing#performance profiling#hypothesis#bisecting#reproduction loop
One-click install
npx skills add https://github.com/yashs33244/my-mac-claude --skill diagnose-yashs33244
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: diagnose
Source: https://github.com/yashs33244/my-mac-claude/tree/main/skills/mattpocock/engineering/diagnose
Command: npx skills add https://github.com/yashs33244/my-mac-claude --skill diagnose-yashs33244

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you systematically diagnose hard bugs and performance regressions by building a fast feedback loop that turns symptoms into actionable evidence.

Core Features & Use Cases

  • Build a measurable feedback loop using failing tests, HTTP/CLI repros, headless browser scripts, trace replay, or minimal harnesses so debugging is grounded in a deterministic signal.
  • Reproduce with correctness checks to ensure you’re observing the exact user-reported failure, and that it’s consistently repeatable (or repeatable at a high-enough rate for flaky issues).
  • Generate falsifiable hypotheses, then instrument precisely by changing one variable at a time, tagging logs for cleanup, and using profiling/bisection for perf regressions.
  • Fix with regression confidence by writing the regression test (when a correct seam exists) before implementing the fix, then re-running the original loop to verify the full scenario.

Quick Start

Ask an AI to diagnose your issue by first constructing a tight repro loop, then running a reproduce → hypothesis → targeted instrumentation → fix → regression-test workflow until the original scenario no longer fails.

Frequently Asked Questions about diagnose

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

FAQPage Schema
How do I debug hard bugs and performance regressions systematically?▼

Debug hard bugs by constructing a deterministic reproduction loop, generating falsifiable hypotheses, and instrumenting with minimal variable changes to convert symptoms into actionable pass/fail evidence.

What's the best way to reproduce flaky bugs for consistent debugging?▼

Reproduce flaky bugs by building a measurable feedback loop using trace replay or minimal harnesses, ensuring the failure repeats at a high enough rate to generate a reliable pass/fail signal.

How do I fix a performance regression using bisection and profiling?▼

Fix performance regressions by running profiling and bisecting to isolate the offending change, then validating the fix by re-running the original reproduction loop to confirm the scenario no longer fails.

Can I use this disciplined debugging loop for wrong outputs and thrown errors?▼

Yes, the disciplined debugging loop applies to broken behavior, thrown errors, and wrong outputs in real codebases by converting those reported symptoms into a reliable pass/fail feedback loop.

Do I need to write a regression test before implementing a bug fix?▼

Yes, write the regression test before implementing the fix when a correct seam exists, then re-run the original reproduction loop to verify the full scenario no longer fails.

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