Systematic Bug Diagnosis — Root Cause, Not Guesswork

Name: Systematic Bug Diagnosis — Root Cause, Not Guesswork
Price: 12 USD
Availability: InStock
Author: Agensi

by Vivek K

Finds why an app bug is happening using a step-by-step method (reproduce, isolate, test ideas, 5 Whys), then gives a small correct fix and a regression test — without guessing first.

$12

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See it in action

You say

ends UTC (Z); API TZ=America/Chicago Symptom: 8h shift stored as 13.0h; naive unit tests pass

clock_out: started = started.astimezone().replace(tzinfo=None) # local wall ended = ended.replace(tzinfo=None) # UTC wall kept hours = (ended - started) / 3600

log: 08:00Z–16:00Z → hours_computed = 13.0

Your agent does

Class: environment | Stage: FIX | Confidence: CONFIRMED | Reproducible: yes

H3 CONFIRMED: asymmetric normalize start → Chicago wall (08:00Z → 03:00) end → UTC wall kept (16:00) → 13.0h lie; true UTC delta = 8.0

Root cause: duration mixed local-converted start with UTC-stripped end Fix: both sides astimezone(UTC) before subtract Regression: clock_out(08:00Z, 16:00Z) asserts 8.0

What you get

Failing test or wrong output with no obvious cause“Works on my machine” / prod-only behaviourRegression after a deploy or mobile client changeIntermittent bugs that need hypothesis trackingHand off a root-cause writeup + regression test to the team

About this skill

The problem

Guessing at fixes wastes hours and often papers over the real cause.
Symptoms (wrong hours, weird totals, flaky tests) get “fixed” in the UI while the root bug stays.
Teams need a shared, evidence-first debugging process — not another “try this” chat.

What it does

Runs a scientific debugging workflow: reproduce → isolate → hypothesize → test → root cause → fix → verify.
Classifies the bug (logic, state, type, race, environment, integration, data, regression) and picks a matching strategy.
Tracks hypotheses with evidence for/against and a next experiment for each.
Builds a 5-Whys chain that separates the symptom from the root cause.
Proposes a minimal fix plus a regression test, with honest confidence: CONFIRMED / PROBABLE / SPECULATIVE.

Frameworks & tools

Language-agnostic method; works on any stack when you provide code, errors, and context.
Uses failing tests, logs, and diffs you already have — no special SaaS debugger required.
SKILL.md workflow for Claude Code, Cursor, Codex CLI, OpenClaw, and similar agents.

Why this beats prompting it yourself

Anti-guessing rule: no “the answer” fix until the cause is CONFIRMED or PROBABLE.
If it cannot reproduce, you get a reproduction plan — not a random patch.
Hypothesis table and 5 Whys keep the investigation honest and reviewable.
Bug-class strategies (e.g. race vs environment) change how it debugs.
Regression test is part of the deliverable so the bug stays fixed.