systematic-debugging
Skill24 starsChanged 24 days agoMITView on GitHub
Use when encountering any bug, test failure, or unexpected behavior. Enforces root-cause investigation before fixes. The Iron Law — no fixes without understanding why.
190 other projects use a version of this, 3 of them edited.
Adopted by
Most recently taken up by
- DemonDamon/AgenticXtheir own version, first seen Nov 9, 2026
- chrysogonus/power-agentstheir own version, first seen Nov 8, 2026
- willy92wins/DayZ-Modding-Knowledge-Packtheir own version, first seen Nov 8, 2026
- roundpilot/superpowers-antigravitytheir own version, first seen Nov 8, 2026
- REPOZY/superpowers-optimizedtheir own version, first seen Nov 8, 2026
- lingyired/status-triotheir own version, first seen Nov 8, 2026
Used with
Projects with it also use chinese-code-review, chinese-commit-conventions and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
Leodorareluctant259Skillchinese-code-review
中文代码审查规范——在保持专业严谨的同时,用符合国内团队文化的方式给出有效反馈
Also in 8 projects that use this
Leodorareluctant259Skillchinese-commit-conventions
中文 Git 提交规范 — 适配国内团队的 commit message 规范和 changelog 自动化
Also in 8 projects that use this
obraSkilldiagnosing-superpowers
Use when a superpowers session went wrong and your human partner wants to know why — repeated work, ignored plans, stumbles, poor results, a skill that didn't fire, "it took too long", "why is it so expensive", "what is it doing" — or wants to build a bug report for the superpowers maintainers, for the current session or a past one identified by id or path, on any harness.
Also in 20 projects that use this
mjunaidcaSkillbuilding-chatgpt-apps
Guides creation of ChatGPT Apps with interactive widgets using OpenAI Apps SDK and MCP servers. Use when building ChatGPT custom apps with visual UI components, embedded widgets, or rich interactive experiences. Covers widget architecture, MCP server setup with FastMCP, response metadata, and Developer Mode configuration. NOT when building standard MCP servers without widgets (use building-mcp-servers skill instead).
Also in 4 projects that use this
mjunaidcaSkillbuilding-chat-interfaces
Build AI chat interfaces with custom backends, authentication, and context injection. Use when integrating chat UI with AI agents, adding auth to chat, injecting user/page context, or implementing httpOnly cookie proxies. Covers ChatKitServer, useChatKit, and MCP auth patterns. NOT when building simple chatbots without persistence or custom agent integration.
Also in 4 projects that use this
- +2 more from Leodorareluctant259
- +5 more from mjunaidca
Other versions190 projects use a version of this.
Word for word · 0
None found.
Edited · 3
- itseffi/agentic-os★ 11415% same
- danielcherubini/skills★ 1414% same
- yeaight7/agent-powerups★ 610% same
Wrote their own version · 187
- obra/superpowers★ 314ksame name
- NousResearch/hermes-agent★ 262ksame name
- open-metadata/OpenMetadata★ 16ksame name
- jnMetaCode/superpowers-zh★ 8.4ksame name
- vudovn/ag-kit★ 8.2ksame name
- vudovn/antigravity-kit★ 8.2ksame name
- openai/plugins★ 7.8ksame name
- ChrisWiles/claude-code-showcase★ 6.1ksame name
- farm-fe/farm★ 5.6ksame name
- microsoft/FluidFramework★ 4.9ksame name
177 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository22 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .claude/rules/agents.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- api-contract-firstSkill
- architecture-auditSkill
- brainstormingSkill
- data-migrationSkill
- dispatching-parallel-agentsSkill
- executing-plansSkill
- finishing-a-development-branchSkill
- five-whysSkill
- incident-responseSkill
- performance-auditSkill
- skill-duplication-auditSkill
- smart-initSkill
- subagent-driven-developmentSkill
- test-driven-developmentSkill
- using-a-teamSkill
- using-git-worktreesSkill
- verification-before-completionSkill
- writing-plansSkill
- writing-skillsSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 177 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 36
Read reference implementations completely — don't skim
- Distinctive: line 45
Verify: works → Phase 4; doesn't work → form NEW hypothesis
- Distinctive: line 49
Write a failing test case that reproduces the bug (before fixing)
- Distinctive: line 51
Verify: test passes, no other tests broken, issue resolved
“Common” is measured: kept by at least 6 in 10 of the 177 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Systematic Debugging
The Iron Law
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRSTQuick patches mask underlying issues. Systematic debugging is FASTER than thrashing.
The Four Phases (Must Complete in Order)
Phase 1: Root Cause Investigation (MANDATORY)
- Read Error Messages Carefully — full stack traces, exact line numbers
- Reproduce Consistently — if not reproducible, gather more data before proceeding
- Check Recent Changes — git diff, recent commits, new dependencies
- Gather Evidence (Multi-Component Systems)
For EACH component boundary: - Log what data enters the component - Log what data exits the component - Verify environment/config propagation Run once to gather evidence showing WHERE it breaks - Trace Data Flow — where does the bad value originate? trace backward
Phase 2: Pattern Analysis
- Find working examples of similar code in the same codebase
- Read reference implementations completely — don't skim
- List every difference between working and broken
- Understand all dependencies and assumptions
Phase 3: Hypothesis and Testing
- Form one specific hypothesis: "I think X is the root cause because Y"
- Make the smallest possible change to test it
- One variable at a time — never multiple changes simultaneously
- Verify: works → Phase 4; doesn't work → form NEW hypothesis
Phase 4: Implementation
- Write a failing test case that reproduces the bug (before fixing)
- Implement the single fix addressing the root cause
- Verify: test passes, no other tests broken, issue resolved
- If 3+ fixes failed → STOP. Question the architecture.
When 3+ Fixes Fail
This is an architectural problem, not a surface bug:
- Each fix reveals new coupling/shared state elsewhere
- Fixes require "massive refactoring" to implement
- Stop and discuss with the human before attempting more fixes
Red Flags — Return to Phase 1
- "Quick fix for now, investigate later"
- "Just try changing X and see if it works"
- "I don't fully understand but this might work"
- "One more fix attempt" (after already trying 2+)
- Proposing solutions before tracing data flow
Real-World Impact
- Systematic: 15-30 minutes to fix, 95% first-time fix rate
- Random fixes: 2-3 hours of thrashing, 40% first-time fix rate
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

