code-doctor
Diagnose structural problems in any codebase — god classes, circular dependencies, complexity violations, SOLID anti-patterns.
Skill by Agent Skill Creator
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/kubementat-code-doctor
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: agent-building
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/code-doctor
What's inside
- Skill name
code-doctor- Description
- Diagnose structural problems in any codebase — god classes, circular dependencies, complexity violations, SOLID anti-patterns. Produces agent-actionable findings with severity, code context, recommended fixes, and example diffs. Offers to start subagents to fix issues.
- License
- MIT
- Metadata
- author: Agent Skill Creator · created: 2026-06-23 · version: 1.0.0 · last_reviewed: 2026-06-23 · review_interval_days: 90
- Instructions
- 166 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (2)
- SKILL.md
- orchestrator.py · scripts/
SKILL.md (first lines)
# /code-doctor — Code Quality Diagnosis You are a code quality doctor. Your job is to diagnose structural problems in any codebase — god classes, circular dependencies, complexity violations, SOLID anti-patterns, and encapsulation issues. You produce agent-actionable findings that another coding agent can use to improve the codebase. ## Trigger User invokes `/code-doctor` followed by their input: ``` /code-doctor Check the codebase /code-doctor --check lint Check only lint issues /code-doctor --check complexity Check only complexity /code-doctor --check design Check only design patterns ``` ## Workflow ### Step 1: Detect Project (Subagent) Spawn a subagent to detect the project language by scanning for language indicators: - `requirements.txt` or `pyproject.toml` → Python - `package.json` → JavaScript/TypeScript - `go.mod` → Go - `pom.xml` or `build.gradle` → Java If no dependency file is found, check for source file extensions. If still no detection, ask the user. ### Step 2: Install Missing Tools (Subagent) Spawn a subagent to install missing tools. For each required tool, check if it's installed. If not, add it to the project's dev dependencies with major version pinning (e.g., `radon>=5.0,<6.0`). Commit the changes. ### Step 3: Pass 1 — Scouting (Parallel, Tooling-Heavy) Spawn four parallel subagents: - `/lint-scout` — Run language-specific linters - `/complexity-scout` — Run complexity tools - `/structure-scout` — Run structural checks (method length, class size, file size) - `/dependency-scout` — Run dependency analysis Each subagent uses the appropriate tool for the detected language(s). Results are collected and aggregated. ### Step 4: Pass 2 — Design Analysis (LLM, Only Flagged Items) For each item flagged in Pass 1, the LLM analyzes with a tailored prompt: - God class → "Analyze for concern mixing, suggest extraction into separate classes" - Feature envy → "Analyze for methods that reach into other classes too much, suggest moving methods" - SOLID violation → "Analyze for Single Responsibility and Open/Closed violations" - Encapsulation issue → "Analyze for fields accessible from too many places" Context for the LLM: flagged item + its imports + classes that import it (1-level deep). ### Step 5: Report Output a structured summary to the console: ``` 🏥 Code Doctor — Diagnosis Report ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 Summary Total issues: 23 🔴 Errors: 5 (must fix) 🟡 Warnings: 12 (should fix) 🔵 Info: 6 (nice-to-have) 🏆 Top Issues ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1. 🔴 God Class — src/services/user_service.py:1 UserService has 23 methods mixing data access, business logic, and formatting 2. 🔴 Circular Dependency — src/models/user.py ↔ src/models/order.py User references Order, Order references User — consider a third model 3. 🔴 Long Method — src/services/user_service.py:150 process_user_data is 127 lines — extract into smaller methods ... Full findings: ./findings.json ``` ### Step 6: Fix Phase (Optional) After the report, ask the user if they want to fix issues: ``` Would you like me to start subagents to fix these issues? 1. Fix all 🔴 errors (5 issues) 2. Fix 🔴 errors and 🟡 warnings (17 issues) 3. Fix everything (23 issues) 4. Skip — I'll review the findings first ``` If the user chooses to fix: 1. **Create a new branch** — `git checkout -b code-doctor-fix-YYYYMMDD` so fixes are not done directly on the main or current feature branch 2. Spawn one fix subagent per finding, running in parallel with file-level locking. Each subagent commits its fix as it completes. ``` 🔧 Starting fixes (5 🔴 errors)... 1/5 ✓ Extracted UserRepository from UserService — committed 2/5 ✓ Resolved circular dependency User↔Order — committed 3/5 ✓ Split UserService into UserService + UserFormatter — committed 4/5 ✓ Extracted OrderProcessor from OrderService — committed 5/5 ✓ Extracted PaymentProcessor from PaymentService — committed ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ All fixes complete. 5 files modified, 5 commits created. Branch: code-doctor-fix-20260623 ``` ## Thresholds | Metric | Python | JS/TS | Go | Java | |--------|--------|-------|-----|------| | Max method length | 50 | 40 | 60 | 50 | | Max class length | 300 | 250 | 200 | 300 | | Max class methods | 15 | 12 | 10 | 15 | | Max class dependencies | 5 | 5 | 4 | 5 |
From Kubementat/ai_agent_skills, MIT.
More from Kubementat/ai_agent_skills
- 0.603score
artificial-analysis
Kubementat
Query the Artificial Analysis Data API (artificialanalysis.ai) to compare LLMs side by side, rank models by intelligence / coding / agentic index / speed /…
SkillAFreshness: A★ 2Claude Code +9 - 0.597score
herdr-cli
Kubementat
Expert guide for herdr, the terminal workspace manager for AI coding agents.
SkillAFreshness: A★ 2Claude Code +9 - 0.563score
github-actions-cicd
ai_agent_skills
Expert implementation and optimization of GitHub Actions CI/CD pipelines.
SkillBFreshness: B★ 2Claude Code +9 - 0.554score
gtd-assistant
Kubementat
A GTD-style productivity assistant that combines open loop collection with intelligent brainstorming to generate actionable next steps, priorities, and…
SkillBFreshness: B★ 2Claude Code +9 - 0.512score
gitlab-ci-cd
ai_agent_skills
Expert design, generation, validation, optimization, and troubleshooting of GitLab CI/CD pipelines.
SkillCFreshness: C★ 2Claude Code +9 - 0.512score
docker-cli
Kubementat
Expert Docker CLI reference — containers, images, buildx, compose, networking, volumes, security, multi-platform builds, and troubleshooting.
SkillCFreshness: C★ 2Claude Code +9 - 0.477score
grill-me
Kubementat
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree.
SkillCFreshness: C★ 2Claude Code +9 - 0.448score
ansible
Kubementat
Ansible automation reference for playbooks, roles, inventory, variables, and modules.
SkillDFreshness: D★ 2Claude Code +9 - 0.448score
frontend-web-developer
Manuel Spörer
Expert frontend developer for Next.js 15/16 App Router, React 19, and Tailwind CSS v4.
SkillDFreshness: D★ 2Claude Code +9 - 0.444score
concourse-ci
Netresearch DTT GmbH
Use when working with ANY Concourse CI task: writing pipelines, configuring resources, building images with oci-build-task, troubleshooting failing jobs…
SkillDFreshness: D★ 2Claude Code +9 - 0.443score
code-summarizer
Kubementat
Scouts and summarizes codebases from local directories or GitHub/GitLab URLs.
SkillDFreshness: D★ 2Claude Code +9 - 0.443score
hf-cli
Kubementat
Use the `hf` CLI tool to interact with Hugging Face Hub — downloading models/datasets, uploading files, managing repos, running jobs, and managing…
SkillDFreshness: D★ 2Claude Code +9
Signals
- Stars
- 2
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Sep 13, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 1.0.0
- License
- MIT
- Repository
- github.com/Kubementat/ai_agent_skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Cite this page
code-doctor skill. Agent Mart. https://agentmart.dev/skills/kubementat-code-doctor (last updated 2026-10-24)