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Lcx Contribute Bug Fix

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code-yeongyu
lcx-contribute-bug-fix

Contribute a verified bug fix for LazyCodex, lazycodex-ai, omo-codex, bundled Codex skills, or upstream Codex CLI bugs. Opens a fork PR only for upstream openai/codex; LazyCodex-owned defects become a verified-fix issue on code-yeongyu/lazycodex (never a PR — that repo is a generated distribution mirror). Use when the user asks to fix a bug, contribute a bug fix, contribute to fix bug, open a PR for a bug, or debug and PR a LazyCodex/Codex defect.

Overview

Publishercode-yeongyu
Repositoryoh-my-openagent
Skill namelcx-contribute-bug-fix
Stars
69.1K
Forks
5.7K
Bundled files
2
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by code-yeongyu on GitHub. Read the source before you install it.

Installation

Install the Lcx Contribute Bug Fix AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/code-yeongyu/oh-my-openagent.git /tmp/oh-my-openagent
mkdir -p .claude/skills
cp -r /tmp/oh-my-openagent/packages/omo-codex/plugin/components/lcx/skills/lcx-contribute-bug-fix .claude/skills/lcx-contribute-bug-fix
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lcx Contribute Bug Fix in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Lcx Contribute Bug Fix on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Lcx Contribute Bug Fix is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

lcx-contribute-bug-fix

Use this skill to debug a concrete LazyCodex or Codex defect, implement the smallest correct fix in a fresh temporary workspace, and deliver it. Work in English, keep the body short, and support every claim with runtime or source evidence.

Route ownership the same way as $lcx-report-bug, but the deliverable differs by target:

  • code-yeongyu/lazycodex for LazyCodex, lazycodex-ai, omo-codex, bundled skills, hooks, MCP wiring, installer behavior, marketplace sync, docs, or packaging. Deliverable: a verified-fix issue with the patch embedded. NEVER open a PR or push a branch against this repo — its contents are regenerated from the source tree on every release, so PRs there cannot be merged and will be closed.
  • openai/codex for upstream Codex CLI bugs that reproduce without LazyCodex or come from Codex core behavior. Deliverable: a PR from a fork.

Required Outcome

For openai/codex, create a fork PR that includes:

  • a focused branch from a fresh ${TMPDIR:-/tmp} clone/worktree
  • reproduction logs from before the fix
  • the smallest implementation that fixes the defect
  • verification logs from after the fix
  • apply lazycodex-generated when label management is available
  • the required LazyCodex footer tag Tag: lazycodex-generated
  • cleanup of temporary worktrees and clones

For code-yeongyu/lazycodex, create an issue (never a PR) that includes:

  • reproduction logs from before the fix
  • the root cause with source evidence
  • the verified patch as a unified diff, produced and tested in a fresh ${TMPDIR:-/tmp} clone/worktree
  • verification logs from after the fix
  • the lazycodex-generated label and the footer tag Tag: lazycodex-generated
  • cleanup of temporary worktrees and clones

Required Workflow

  1. Read the user's bug report and identify the affected surface.
  2. Invoke $omo:debugging for the investigation. If only unqualified skill names are exposed, invoke $debugging and state that it is the OMO debugging skill.
  3. Materialize the latest sources under LAZYCODEX_SOURCE_ROOT="${LAZYCODEX_SOURCE_ROOT:-${TMPDIR:-/tmp}/lazycodex-sources}", then decide the target repository. Sync both checkouts on every run and compare them before choosing. Validate cached checkouts before reuse so an incomplete .git directory cannot route the fix to the wrong repo:
bash
LAZYCODEX_SOURCE_ROOT="${LAZYCODEX_SOURCE_ROOT:-${TMPDIR:-/tmp}/lazycodex-sources}"
mkdir -p "$LAZYCODEX_SOURCE_ROOT"

valid_source_checkout() {
  DEST="$1"
  git -C "$DEST" rev-parse --is-inside-work-tree >/dev/null 2>&1 &&
    git -C "$DEST" config --get remote.origin.url >/dev/null 2>&1
}

recover_corrupt_source_checkout() {
  DEST="$1"
  if [ -e "$DEST" ] && ! valid_source_checkout "$DEST"; then
    QUARANTINED="$DEST.corrupt.$(date +%Y%m%d%H%M%S)"
    mv "$DEST" "$QUARANTINED"
    echo "Moved corrupt source cache $DEST to $QUARANTINED" >&2
  fi
}

sync_latest_source() {
  REPO="$1"; DEST="$2"
  recover_corrupt_source_checkout "$DEST"
  if [ ! -d "$DEST" ]; then
    gh repo clone "$REPO" "$DEST" -- --depth=1 \
      || git clone --depth=1 "https://github.com/$REPO" "$DEST"
  fi
  if ! valid_source_checkout "$DEST"; then
    echo "Source cache $DEST is not a usable git checkout after clone" >&2
    return 1
  fi
  git -C "$DEST" remote set-url origin "https://github.com/$REPO.git" >/dev/null 2>&1 || true
  DEFAULT_BRANCH="$(git -C "$DEST" remote show origin | sed -n '/HEAD branch/s/.*: //p')"
  if [ -z "$DEFAULT_BRANCH" ]; then
    DEFAULT_BRANCH="$(git -C "$DEST" symbolic-ref --short refs/remotes/origin/HEAD 2>/dev/null | sed 's#^origin/##')"
  fi
  if [ -z "$DEFAULT_BRANCH" ]; then
    echo "Could not determine default branch for $REPO in $DEST" >&2
    return 1
  fi
  git -C "$DEST" fetch --depth=1 origin "$DEFAULT_BRANCH"
  git -C "$DEST" checkout -B "$DEFAULT_BRANCH" FETCH_HEAD
}
sync_latest_source code-yeongyu/lazycodex "$LAZYCODEX_SOURCE_ROOT/lazycodex-source"
sync_latest_source openai/codex "$LAZYCODEX_SOURCE_ROOT/openai-codex-source"
  1. Create a fresh temporary clone and branch under ${TMPDIR:-/tmp}. Do not modify the user's current repository for the target fix unless the current repository is itself the requested target and the user explicitly asked for local edits.
bash
TARGET_REPO="code-yeongyu/lazycodex" # or openai/codex
WORK_ROOT="$(mktemp -d "${TMPDIR:-/tmp}/lazycodex-fix-XXXXXX")"
gh repo clone "$TARGET_REPO" "$WORK_ROOT/repo" -- --depth=1
cd "$WORK_ROOT/repo"
BASE_BRANCH="$(git remote show origin | sed -n '/HEAD branch/s/.*: //p')"
git fetch origin "$BASE_BRANCH" --depth=1
BRANCH_NAME="lazycodex/bug-fix-<short-slug>"
git worktree add "$WORK_ROOT/worktree" -b "$BRANCH_NAME" "origin/$BASE_BRANCH"
cd "$WORK_ROOT/worktree"

If gh cannot clone, use git clone --depth=1 "https://github.com/$TARGET_REPO" "$WORK_ROOT/repo" and continue with the same worktree flow.

  1. Reproduce the bug in the worktree through the real surface. Save exact command output to ${TMPDIR:-/tmp}/lazycodex-fix-<short-slug>-repro.log.
  2. Write or update a failing regression test before production changes. Confirm it fails for the bug, not for a missing fixture or typo.
  3. Implement the smallest correct fix. Avoid refactors unless the fix cannot be made safely without one.
  4. Run the regression test, adjacent tests, and the smallest real-surface QA command that proves the user-visible behavior changed.
  5. Commit the verified fix in the worktree. Inspect the status first so the delivered diff cannot be empty or stale:
bash
git status --short
git add -A
git commit -m "fix: <short bug-fix summary>"
git log --oneline "origin/$BASE_BRANCH..HEAD"
  1. Build the delivery body for the target:
  • openai/codex: generate the PR body with scripts/create-pr-body.mjs.
  • code-yeongyu/lazycodex: export the verified patch and write the issue body from the Verified-Fix Issue Template below:
bash
PATCH_FILE="${TMPDIR:-/tmp}/lazycodex-fix-<short-slug>.patch"
git diff "origin/$BASE_BRANCH"..HEAD > "$PATCH_FILE"
  1. Ensure the generated label exists when the target repo allows label management. Keep the footer tag even when label creation is unavailable:
bash
LABEL_ARGS=()
if gh label create lazycodex-generated --repo "$TARGET_REPO" --color "7C3AED" --description "Created by LazyCodex" --force; then
  LABEL_ARGS=(--label lazycodex-generated)
else
  echo "Label management unavailable for $TARGET_REPO; keeping the footer tag only."
fi
  1. Deliver the fix.
  • code-yeongyu/lazycodex: create the verified-fix issue. Never push a branch to this repo and never run gh pr create against it:
bash
ISSUE_BODY="${TMPDIR:-/tmp}/lazycodex-fix-<short-slug>-issue.md"
gh issue create --repo code-yeongyu/lazycodex --title "<short fix title>" "${LABEL_ARGS[@]}" --body-file "$ISSUE_BODY"
  • openai/codex: fork, push the branch to the fork, and create the PR:
bash
gh repo fork openai/codex --remote --remote-name fork
GH_USER="$(gh api user --jq .login)"
git push -u fork "$BRANCH_NAME"
gh pr create --repo openai/codex --base "$BASE_BRANCH" --head "$GH_USER:$BRANCH_NAME" --title "<short fix title>" "${LABEL_ARGS[@]}" --body-file "$PR_BODY"
  1. Clean up:
bash
cd /
git -C "$WORK_ROOT/repo" worktree remove "$WORK_ROOT/worktree"
find "$WORK_ROOT" -mindepth 1 -maxdepth 1 -exec rm -r -- {} +
rmdir "$WORK_ROOT"

Return the PR or issue URL, the reproduction command, the verification command, and the cleanup receipt.

Verified-Fix Issue Template (code-yeongyu/lazycodex)

Write the issue body in English. Embed the patch verbatim so a maintainer can apply it to the source tree:

markdown
## Problem Situation
[What failed for the user.]

## Reproduction Logs
[Exact failing command and relevant log excerpt.]

## Root Cause
[Confirmed cause with runtime and source evidence.]

## Verified Fix
[What changed and why this is the smallest correct fix.]

```diff
[Contents of $PATCH_FILE.]
```

## Verification
- [RED test output or repro before the fix]
- [GREEN test output after the fix]
- [Manual QA command and result]

---
This fix was debugged, implemented, and verified with [LazyCodex](https://github.com/code-yeongyu/lazycodex).
Tag: lazycodex-generated

PR Body Generator (openai/codex)

Use the bundled script to generate the PR body. Create a JSON file with this shape:

json
{
  "title": "Fix short user-visible failure",
  "targetRepository": "openai/codex",
  "problem": "What is broken for the user.",
  "reproductionLogs": "Exact failing command, log excerpt, or trace.",
  "approach": "What changed and why this is the smallest correct fix.",
  "confidence": "Why the diagnosis and fix are strongly supported.",
  "risks": "Risk level and what could regress.",
  "userVisibleBehaviorChanges": "What changes for the user after the PR.",
  "verification": ["failing test before fix", "passing test after fix", "manual QA command"]
}

Run:

bash
PR_INPUT="${TMPDIR:-/tmp}/lazycodex-fix-<short-slug>-pr.json"
PR_BODY="${TMPDIR:-/tmp}/lazycodex-fix-<short-slug>-pr.md"
node "<skill-root>/scripts/create-pr-body.mjs" "$PR_INPUT" "$PR_BODY"

PR Body Template (openai/codex)

The generated body must follow this structure:

markdown
## Problem Situation
[What failed for the user.]

## Reproduction Logs
[Exact failing command and relevant log excerpt.]

## Approach
[What changed and why.]

## Why I Am Confident
[Evidence that proves the root cause and fix.]

## Risks
[Risk level and possible regressions.]

## User-Visible Behavior Changes
[What users experience after this PR.]

## Verification
- [RED test output or repro before the fix]
- [GREEN test output after the fix]
- [Manual QA command and result]

---
This PR was debugged, implemented, and created with [LazyCodex](https://github.com/code-yeongyu/lazycodex).
Tag: lazycodex-generated

Stop Conditions

Stop and ask one narrow question only when:

  • the bug cannot be reproduced from available information
  • target repository ownership remains ambiguous after comparing LazyCodex and upstream Codex evidence
  • authentication is missing for creating the issue or pushing and creating the PR
  • the fix requires a product decision rather than a technical correction

Do not open:

  • a PR or pushed branch targeting code-yeongyu/lazycodex — deliver the verified-fix issue instead, always
  • a PR or verified-fix issue without a failing-before and passing-after test
  • a PR or verified-fix issue without a real-surface QA command
  • a PR or issue without the Tag: lazycodex-generated footer
  • a verified-fix issue without the patch embedded in a diff block
  • a vague fix that does not identify the root cause
  • a broad refactor disguised as a bug fix

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Lcx Contribute Bug Fix AI skill do?

Contribute a verified bug fix for LazyCodex, lazycodex-ai, omo-codex, bundled Codex skills, or upstream Codex CLI bugs. Opens a fork PR only for upstream openai/codex; LazyCodex-owned defects become a verified-fix issue on code-yeongyu/lazycodex (never a PR — that repo is a generated distribution mirror). Use when the user asks to fix a bug, contribute a bug fix, contribute to fix bug, open a PR for a bug, or debug and PR a LazyCodex/Codex defect.

Why use Lcx Contribute Bug Fix on TypingMind?

Because you install it once and use it with any model. Lcx Contribute Bug Fix is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Lcx Contribute Bug Fix in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/code-yeongyu/oh-my-openagent/tree/dev/packages/omo-codex/plugin/components/lcx/skills/lcx-contribute-bug-fix. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Lcx Contribute Bug Fix?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Lcx Contribute Bug Fix?

As many as you like. As long as a model supports skills, you can use Lcx Contribute Bug Fix with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Lcx Contribute Bug Fix AI skill free?

It is published on GitHub by code-yeongyu. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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