Eval Code Quality logo

Eval Code Quality

Community
Ibrahim-3d
eval-code-quality

Specialized code quality evaluator for the Evaluate-Loop. Use this for evaluating code implementation tracks where the deliverable is functional code — features, API routes, state management, utilities. Checks build integrity, type safety, code patterns, error handling, dead code, imports, test coverage, and naming conventions. Dispatched by loop-execution-evaluator when track type is 'feature', 'refactor', or 'infrastructure'. Triggered by: 'evaluate code', 'code review', 'quality check', 'build check'.

Overview

PublisherIbrahim-3d
Repositoryorchestrator-supaconductor
Skill nameeval-code-quality
Stars
378
Forks
38
Bundled files
Instructions only
LicenseAGPL-3.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Ibrahim-3d on GitHub. Read the source before you install it.

Installation

Install the Eval Code Quality 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/Ibrahim-3d/orchestrator-supaconductor.git /tmp/orchestrator-supaconductor
mkdir -p .claude/skills
cp -r /tmp/orchestrator-supaconductor/skills/eval-code-quality .claude/skills/eval-code-quality
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Eval Code Quality 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 Eval Code Quality 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 Eval Code Quality 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.

Code Quality Evaluator Agent

Specialized evaluator for tracks whose deliverables are functional code — features, state management, utilities, API routes.

When This Evaluator Is Used

Dispatched by loop-execution-evaluator when the track is one of:

  • Feature implementation (e.g., user authentication, data processing)
  • Infrastructure/utility work
  • Refactoring tracks
  • State management (Zustand, hooks)

Inputs Required

  1. Track's spec.md and plan.md
  2. Changed files (from plan.md task summaries or git diff)
  3. tsconfig.json — TypeScript config
  4. package.json — dependencies and scripts
  5. Existing test files (if any)

Evaluation Passes (6 checks)

Pass 1: Build Integrity

bash
npm run build    # Must exit 0
npx tsc --noEmit # Must exit 0 (no type errors)
markdown
### Build: PASS ✅ / FAIL ❌
- Build status: [success / X errors]
- Type check: [clean / X type errors]
- Errors: [list if any]

Pass 2: Type Safety

CheckWhat to Look For
No any typesExplicit typing on all exports, function params, return types
Generic usageAPI responses typed with ApiResponse<T>
Null safetyOptional chaining (?.) or null checks where data may be absent
Type exportsShared types in src/types/, not inline
Interface consistencyTypes match spec/product.md schema
markdown
### Type Safety: PASS ✅ / FAIL ❌
- `any` usage: [count] — [list files:lines]
- Missing types: [list untyped exports]
- Null safety issues: [list]

Pass 3: Code Patterns & State Management

CheckWhat to Look For
File structureFiles in correct directories per component architecture
Namingkebab-case files, PascalCase components, {Component}Props
ImportsNo circular imports, no unused imports
DRYNo significant code duplication (>10 lines repeated)
Single responsibilityFunctions/components do one thing
Module boundariesFeature code in feature dirs, shared code in ui/ or lib/
State syncEvery client state mutation has corresponding API endpoint
Optimistic updatesRollback logic present on API failure
Source of truthServer (DB) is source of truth, client is cache

State Sync Anti-Patterns to Flag:

typescript
// ❌ BAD: State updated without API persistence
const toggleLock = (id) => {
  set({ assets: { ...assets, [id]: { locked: true } } });
  // No API call!
}

// ✅ GOOD: Optimistic update with API sync
const toggleLock = async (id) => {
  const prev = assets;
  set({ assets: { ...assets, [id]: { locked: true } } }); // Optimistic
  try {
    await fetch(`/api/assets/${id}`, {
      method: 'PATCH',
      body: JSON.stringify({ locked: true })
    });
  } catch (err) {
    set({ assets: prev }); // Rollback
    throw err;
  }
}
markdown
### Code Patterns & State Sync: PASS ✅ / FAIL ❌
- Naming violations: [list]
- Unused imports: [list files]
- Duplication found: [describe]
- **State mutations without API: [count] — [list]**
- **Missing rollback logic: [count] — [list]**
- **API endpoints without client updates: [count] — [list]**

Pass 4: Error Handling

CheckWhat to Look For
API callstry/catch or error handling on all async operations
User feedbackToast/inline error shown to user on failure
Null dataEmpty states handled (no data, loading, error)
Edge casesInvalid input, network failure, timeout
No silent failuresErrors not swallowed without user notification
markdown
### Error Handling: PASS ✅ / FAIL ❌
- Unhandled async: [list functions]
- Missing user feedback: [list scenarios]
- Silent failures: [list]

Pass 5: Dead Code & Cleanup

CheckWhat to Look For
Unused exportsFunctions/components exported but never imported
Commented codeLarge blocks of commented-out code (should be deleted)
Unused filesFiles that exist but aren't imported anywhere
TODO/FIXMEUnresolved TODO comments
Console logsconsole.log left in production code
markdown
### Dead Code: PASS ✅ / FAIL ❌
- Unused exports: [list]
- Console logs: [list files:lines]
- TODOs: [list]

Pass 6: Test Coverage (when applicable)

CheckTarget
Overall coverage70%
Business logic90%
API routes80%
Utility functions80%
markdown
### Tests: PASS ✅ / FAIL ❌ / ⚠️ NOT CONFIGURED
- Coverage: [X]% overall
- Business logic: [X]%
- Untested critical paths: [list]

Verdict Template

markdown
## Code Quality Evaluation Report

**Track**: [track-id]
**Evaluator**: eval-code-quality
**Date**: [YYYY-MM-DD]
**Files Evaluated**: [count]

### Results
| Pass | Status | Issues |
|------|--------|--------|
| 1. Build | PASS/FAIL | [details] |
| 2. Type Safety | PASS/FAIL | [count] issues |
| 3. Code Patterns | PASS/FAIL | [count] issues |
| 4. Error Handling | PASS/FAIL | [count] issues |
| 5. Dead Code | PASS/FAIL | [count] issues |
| 6. Tests | PASS/FAIL/N/A | [coverage] |

### Verdict: PASS ✅ / FAIL ❌
[If FAIL, list specific fix actions for loop-fixer]

Handoff

  • PASS → Return to loop-execution-evaluator → Conductor marks complete
  • FAIL → Return to loop-execution-evaluator → Conductor dispatches loop-fixer

Frequently asked questions

What does the Eval Code Quality AI skill do?

Specialized code quality evaluator for the Evaluate-Loop. Use this for evaluating code implementation tracks where the deliverable is functional code — features, API routes, state management, utilities. Checks build integrity, type safety, code patterns, error handling, dead code, imports, test coverage, and naming conventions. Dispatched by loop-execution-evaluator when track type is 'feature', 'refactor', or 'infrastructure'. Triggered by: 'evaluate code', 'code review', 'quality check', 'build check'.

Why use Eval Code Quality on TypingMind?

Because you install it once and use it with any model. Eval Code Quality 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 Eval Code Quality in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Ibrahim-3d/orchestrator-supaconductor/tree/master/skills/eval-code-quality. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Eval Code Quality?

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 Eval Code Quality?

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

Is the Eval Code Quality AI skill free?

Yes. It is published on GitHub by Ibrahim-3d under the AGPL-3.0 license. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇