diagnose

Diagnose bugs and performance regressions through a structured reproduce-hypothesise-fix workflow.

20|2|Updated May 16, 2026
One-click install
npx skills add https://github.com/reddb-io/red-skills --skill diagnose-reddb-io
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: diagnose
Source: https://github.com/reddb-io/red-skills/tree/main/plugins/dev/skills/engineering/diagnose
Command: npx skills add https://github.com/reddb-io/red-skills --skill diagnose-reddb-io

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Hard bugs and performance regressions often lead developers to guess at fixes without reproducing the failure, wasting time and shipping unverified patches. This Skill enforces a disciplined diagnosis loop so every fix is grounded in a reproducible failure and locked down by a regression test. ## Core Features & Use Cases - Feedback loop construction: Builds a fast, deterministic pass/fail signal first using ten strategies, from failing tests and curl scripts to replayed traces and bisection harnesses. - Ranked falsifiable hypotheses: Generates 3-5 ranked, falsifiable hypotheses before testing, with optional recall of past root causes from the memory plugin. - Instrumented fix and regression test: Changes one variable at a time with tagged debug logs, writes the regression test before the fix, and finishes with cleanup and a post-mortem. - Use Case: A user reports that an API endpoint intermittently returns stale data after a deploy. The Skill loops the trigger 100 times to raise the reproduction rate, ranks caching-layer hypotheses, instruments the boundary, and lands a fix with a failing-then-passing regression test. ## Quick Start Ask the agent to diagnose the bug where the checkout endpoint intermittently returns stale totals after the latest deploy.

Frequently Asked Questions about diagnose

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

FAQPage Schema
How do I debug a bug that is hard to reproduce?▼

Build a feedback loop first: a fast, deterministic pass/fail signal such as a failing test, curl script, or replayed trace. For non-deterministic bugs, loop the trigger 100 times, parallelise, and add stress to raise the reproduction rate before hypothesising.

How to diagnose a performance regression in code?▼

Establish a baseline measurement with a timing harness, profiler, or query plan, then bisect to find the regression point. Logs are usually the wrong tool for performance work; measure first and fix second.

What should I do when I cannot reproduce a bug locally?▼

Stop and say so explicitly, listing what you tried. Ask the user for environment access, a captured artifact such as a HAR file or log dump, or permission to add temporary production instrumentation instead of guessing.

Does this debugging workflow require the memory plugin?▼

No, memory recall is optional and best-effort. If the memory plugin is installed, past root causes are recalled to seed hypotheses; if absent, the diagnosis proceeds normally and the check skips silently.

Why write a regression test before applying the fix?▼

Writing the test first proves it exercises the real bug pattern by watching it fail, then confirms the fix by watching it pass. If no correct test seam exists, that architectural gap is itself a finding to flag.