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refpathrefpath/chatgpt-team/.agents/skills/systematic-debugging/SKILL.md

systematic-debugging

Skill0 starsChanged 2 months agoMITView on GitHub

Diagnose a reproducible defect, regression, or flaky check by testing causal explanations before patching. Use for investigating failures, not routine feature implementation.

190 other projects use a version of this.

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Most recently taken up by

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.
  • Leodorareluctant259Skill

    chinese-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

  • Leodorareluctant259Skill

    chinese-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

  • obraSkill

    diagnosing-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

  • mjunaidcaSkill

    building-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

  • mjunaidcaSkill

    building-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

The file

We split this skill into the rules it gives an agent

2 rules. 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 177 edited versions we read keep these.

  • 2

    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
  1. Distinctive:

    Use targeted source and Git history to understand a suspicious constraint before removing it.

    line 12
  2. Distinctive:

    Run the original reproducer against the fix, then the relevant regression and repository-required checks.

    line 16

“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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Systematic debugging

Establish expected behavior, observed behavior, the candidate revision, and relevant environment. Preserve the smallest useful reproducer and its actual failure. Distinguish a product defect from a fixture, dependency, command, or environment failure.

Trace the failing value or event through the owning boundaries. State a falsifiable explanation and choose a small probe that distinguishes it from plausible alternatives. Change one causal variable at a time when possible; do not accumulate speculative fixes.

Use targeted source and Git history to understand a suspicious constraint before removing it. If repeated fixes fail, reassess the explanation and missing evidence. When reproduction is unavailable, report that gap rather than claiming an observed root cause.

Engineer implements the causal fix in its assigned worktree. QA preserves independent reproduction and tests in its own worktree and returns production defects to the owner. Retain a still-failing reproducer on the QA branch or in the finding until it is resolved.

Run the original reproducer against the fix, then the relevant regression and repository-required checks. Report the failing baseline, cause supported by evidence, change, fresh result, and remaining uncertainty. Redact sensitive data from diagnostic output.

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