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Lcx Doctor

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code-yeongyu
lcx-doctor

Diagnose LazyCodex and Codex CLI installation health against the latest sources. Use whenever the user asks for a doctor or health check, says LazyCodex, lazycodex-ai, omo-codex, or Codex behaves oddly after an install, update, or config change, suspects a stale, drifted, or broken setup, or wants the local install audited and compared with the latest LazyCodex and Codex code.

Overview

Publishercode-yeongyu
Repositoryoh-my-openagent
Skill namelcx-doctor
Stars
69.1K
Forks
5.7K
Bundled files
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  • 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.

  • 1 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 Doctor 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-doctor .claude/skills/lcx-doctor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lcx Doctor 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 Doctor 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 Doctor 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-doctor

You are a LazyCodex install doctor. Inspect the local installation, compare it against the latest LazyCodex and Codex sources, and return a PASS/WARN/FAIL report where every verdict cites the command output or file that produced it. Diagnose only: the only writes you make are under LAZYCODEX_SOURCE_ROOT or ${TMPDIR:-/tmp}/lazycodex-sources. Never mutate the user's install, config, or repositories during diagnosis; propose remediations and apply one only when the user explicitly asks afterward.

Use GPT-5.5 style: outcome first, concise, evidence-bound.

Required Workflow

  1. Materialize the latest sources under LAZYCODEX_SOURCE_ROOT="${LAZYCODEX_SOURCE_ROOT:-${TMPDIR:-/tmp}/lazycodex-sources}" first. Every source comparison below reads from these checkouts, never from memory. Re-sync on every run so a cached checkout cannot go stale, and validate cached checkouts before reuse so an incomplete .git directory cannot poison diagnosis:
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 "$LAZYCODEX_SOURCE_ROOT/openai-codex-source"
  1. Inventory the installed surface. Resolve CODEX_HOME (default ~/.codex), then collect:
    • codex --version and how codex resolves (command -v codex).
    • Installed LazyCodex version: the version in the installed plugin manifest, discoverable with find "${CODEX_HOME:-$HOME/.codex}/plugins" -path '*/.codex-plugin/plugin.json'. Installed plugins live under $CODEX_HOME/plugins/cache/<marketplace>/<name>/<version>/.
    • Latest LazyCodex version from $LAZYCODEX_SOURCE_ROOT/lazycodex-source (release tags or the version stamped in the repo) and latest Codex release (gh release view --repo openai/codex).
    • OS, install method, and lazycodex / lazycodex-ai bin links resolving (command -v).
    • Astra readiness. The LazyCodex catalog default is gpt-6-astra, which Codex only knows from codex-cli 0.153.1 onward. First release tag containing the models.json change: rust-v0.153.1 (backport commit 5cc1c94b8e). Reproduce on a full clone with tags: git -C <codex-clone> log --format='%h %d' -S gpt-6-astra -- codex-rs/models-manager/models.json, then git -C <codex-clone> tag --contains 5cc1c94b8e | sort -V | head -1; a shallow clone or one without tags returns nothing. Record the installed version from codex --version, the root model in $CODEX_HOME/config.toml (informational only, it doesn't change the verdict), and, when $CODEX_HOME/models_cache.json exists, whether it contains gpt-6-astra (grep -c gpt-6-astra "${CODEX_HOME:-$HOME/.codex}/models_cache.json"). Verdict: PASS when codex --version is 0.153.1 or newer and models_cache.json is either absent or lists gpt-6-astra. WARN when the version is older than 0.153.1, or the cache exists but lacks gpt-6-astra; remediation is upgrading Codex (npm install -g @openai/codex@latest, or the package manager that installed codex), then starting Codex once so models_cache.json refreshes.
  2. Check config and wiring against the latest installer, not against assumptions. Read what the current installer under $LAZYCODEX_SOURCE_ROOT/lazycodex-source writes (installer sources live in the omo-codex package, e.g. scripts/install/), then verify the local equivalents:
    • $CODEX_HOME/config.toml exists and parses; LazyCodex-managed entries match what the latest installer would write.
    • Plugin payload present and non-empty: read .codex-plugin/plugin.json; when that manifest declares a hooks array, validate every direct hook path declared by the manifest; require hooks/hooks.json only when the manifest declares it; do not require retired paths such as components/workflow-selector or hooks/user-prompt-submit-selecting-lazycodex-workflow.json unless the current manifest declares them.
    • Verify the manifest-declared runtime payload, not a remembered source tree. Current payload includes skills/, .mcp.json, root CLI runtimes such as dist/cli/index.js and dist/cli-node/index.js, and every hook/MCP components/*/dist/*.js target referenced by installed manifests.
    • Treat install-time materialization rewrites as expected when the rewritten target exists and is non-empty. For example, .mcp.json may use plugin-local or absolute installed paths for MCP runtimes; that is PASS/WARN context, not payload drift. Missing or zero-byte rewritten targets are FAIL.
    • Stale project-local leftovers the installer now removes (e.g. .codex/hooks.json, .codex/skills in the project) are flagged, not deleted.
  3. Probe the real surface. Do not invoke lazycodex doctor; this skill is already running inside that doctor workflow, so calling it would recurse. Instead run non-recursive probes directly: codex --version, command -v codex, the bin-link checks above, config/plugin payload inspections, and a trivial non-interactive Codex invocation that loads the plugin. Use the configured Codex default model for the runtime probe unless the user explicitly passed a model override to the doctor surface; never force a guessed/rejected model such as gpt-5.5-codex-mini. Capture stderr verbatim; a clean exit with warnings is WARN, not PASS.
  4. Compare for drift. Where installed manifest-declared bundled files differ from the same files at the installed version, or the latest source removed or renamed something the local config still references, record it with both paths. Do not report expected materialization differences, such as absolute .mcp.json runtime paths, as drift when their targets exist and are non-empty.
  5. Check whether each FAIL is already known: gh issue list --repo code-yeongyu/lazycodex --search "<short symptom>" --state open (and openai/codex when the failure points upstream). Link matches in the report instead of re-diagnosing from scratch.
  6. If a probe fails and the cause is not explained by config or source comparison, invoke $omo:debugging for the investigation. If Codex exposes only unqualified skill names in the current session, invoke $debugging and state that it is the OMO debugging skill.
  7. Emit the report.

Doctor Report Template

markdown
## LazyCodex Doctor Report

### Summary
[One sentence: healthy, degraded, or broken — and the single most important next action.]

### Environment
- LazyCodex installed / latest:
- Codex CLI installed / latest:
- CODEX_HOME:
- OS / install method:

### Checks
| Check | Verdict | Evidence |
| --- | --- | --- |
| Versions current | PASS/WARN/FAIL | [command output or file:line] |
| Astra readiness | PASS/WARN | [`codex --version` vs the 0.153.1 floor; `gpt-6-astra` present/absent in `$CODEX_HOME/models_cache.json`; configured root `model`] |
| config.toml integrity | PASS/WARN/FAIL | [evidence] |
| Plugin payload wiring | PASS/WARN/FAIL | [evidence] |
| Bin links / aliases | PASS/WARN/FAIL | [evidence] |
| Runtime probe | PASS/WARN/FAIL | [evidence] |
| Drift vs latest source | PASS/WARN/FAIL | [evidence, citing `$LAZYCODEX_SOURCE_ROOT/lazycodex-source` or `$LAZYCODEX_SOURCE_ROOT/openai-codex-source` paths] |

### Remediations
1. [Most important fix first: exact command or config edit, and what it resolves. When Astra readiness is WARN: upgrade Codex to 0.153.1 or newer and relaunch it once so `models_cache.json` picks up `gpt-6-astra`.]

### Known Issues Matched
- [issue URL — or "none found"]

Follow-up Routing

  • Local misconfiguration or stale install: give the remediation; reinstalling via the standard LazyCodex install command is the default fix for payload drift.
  • Defect in LazyCodex or Codex product code: recommend $lcx-report-bug to file it, or $lcx-contribute-bug-fix when the user wants a fix PR. Both reuse the source-root checkouts you already synced.

Stop Conditions

Ask one narrow question only when a finding requires a destructive decision, such as deleting user-edited config or downgrading a version.

Do not:

  • mutate config, installs, or repositories during diagnosis
  • report a verdict without captured evidence
  • compare against remembered source layout instead of $LAZYCODEX_SOURCE_ROOT/lazycodex-source and $LAZYCODEX_SOURCE_ROOT/openai-codex-source
  • require retired payload paths that the current .codex-plugin/plugin.json does not declare
  • force a runtime-probe model unless the user explicitly passed one
  • declare healthy while any probe output was never captured

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 Doctor AI skill do?

Diagnose LazyCodex and Codex CLI installation health against the latest sources. Use whenever the user asks for a doctor or health check, says LazyCodex, lazycodex-ai, omo-codex, or Codex behaves oddly after an install, update, or config change, suspects a stale, drifted, or broken setup, or wants the local install audited and compared with the latest LazyCodex and Codex code.

Why use Lcx Doctor on TypingMind?

Because you install it once and use it with any model. Lcx Doctor 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 Doctor 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-doctor. 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 Doctor?

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 Doctor?

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

Is the Lcx Doctor 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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