ce-debug

Diagnose root causes of bugs and implement test-first fixes through a phased investigation workflow.

Updated May 11, 2026
One-click install
npx skills add https://github.com/mmnavarr/harness --skill ce-debug-mmnavarr
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ce-debug
Source: https://github.com/mmnavarr/harness/tree/main/skills/ce-debug
Command: npx skills add https://github.com/mmnavarr/harness --skill ce-debug-mmnavarr

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Debugging often devolves into guessing, shotgun changes, and symptom patches that leave the real root cause active. This Skill enforces a disciplined investigate-before-fixing workflow that traces the full causal chain from trigger to symptom before any code is changed. ## Core Features & Use Cases - Phased investigation framework: Triage, reproduce, trace the code path, form evidence-grounded hypotheses with testable predictions, then fix test-first with workspace safety checks. - Issue tracker integration: Fetches full issue threads from GitHub, Linear, or Jira to extract symptoms, reproduction steps, and prior failed attempts. - Deep reference playbooks: Covers anti-patterns (shotgun debugging, confirmation bias), intermittent bugs, race conditions, heisenbugs, git bisect, and defense-in-depth layering. - Use Case: A user pastes a failing CI stack trace. The Skill reproduces the failure, instruments component boundaries to localize the fault, confirms the root cause with a prediction, writes a failing regression test, applies the minimal fix, and opens a PR that auto-closes the linked issue. ## Quick Start Ask the AI to debug the pasted error message, failing test path, or issue reference and find its root cause before fixing it.

Frequently Asked Questions about ce-debug

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

FAQPage Schema
How do I debug a failing test systematically instead of guessing?▼

Reproduce the failure first, then trace the code path backward from the symptom to where valid state first became invalid. Form hypotheses grounded in observed values, test one change at a time, and confirm the full causal chain before editing code.

How to find the root cause of a bug from a GitHub issue?▼

Fetch the full issue thread with gh issue view including all comments, since later comments often contain narrowed reproduction steps or prior failed attempts. Extract symptoms and environment details, then reproduce the bug before tracing the code path.

What should I do when a bug does not reproduce reliably?▼

Use intermittent-bug techniques: add logging traps at the suspected failure point, run the scenario in a loop to establish a reproduction rate, isolate environment variables, and check for test-order pollution from leaked state between tests.

Why does my fix work but the bug keeps coming back?▼

A fix that works despite a wrong prediction means you patched a symptom, not the root cause. The real cause is still active. Re-examine the causal chain, explicitly invalidate the prior hypothesis with evidence, and form a new one with its own prediction.

When should I use git bisect for debugging?▼

Use git bisect when the bug is a regression where the code previously worked. Mark the current commit as bad and a known-good commit as good, then let bisect binary-search the breaking commit, optionally automated with a test script.

When is defense-in-depth validation warranted after a bug fix?▼

Apply it when the root-cause pattern appears in three or more other files or the bug would have been catastrophic in production. Add guards at distinct layers such as entry validation, invariant checks, environment guards, and diagnostic breadcrumbs.