# Quality

> Code quality check: linting, complexity analysis, duplication detection, and dead code identification. Detects project linting config, runs appropriate tools, and creates a structured GitHub issue.

- Skill: `rube-de/quality` (Agent Skill)
- Install (CLI): `npx skillmds@latest add rube-de/quality`
- Raw SKILL.md: https://api.skillmd.com/api/skills/rube-de/quality/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: rube-de (https://skillmd.com/u/rube-de)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/rube-de/quality

---


# DLC: Code Quality Check

Run code quality analysis against the current project and create a GitHub issue with findings.

Before running, **read [../dlc/references/ISSUE-TEMPLATE.md](../dlc/references/ISSUE-TEMPLATE.md) now** for the issue format, and **read [../dlc/references/REPORT-FORMAT.md](../dlc/references/REPORT-FORMAT.md) now** for the findings data structure.

## Step 1: Detect Linting Config

Scan for linting configuration and project type:

| Config File | Linter | Language |
|-------------|--------|----------|
| `.eslintrc*` / `eslint.config.*` / `biome.json` | ESLint / Biome | JS/TS |
| `ruff.toml` / `pyproject.toml` (with `[tool.ruff]`) | Ruff | Python |
| `.golangci.yml` / `.golangci.yaml` | golangci-lint | Go |
| `clippy.toml` / `Cargo.toml` | Clippy | Rust |
| `.rubocop.yml` | RuboCop | Ruby |

Also check for formatter configs: `.prettierrc*`, `.editorconfig`, `rustfmt.toml`.

## Step 2: Run Quality Tools

### Linting

Run the detected linter with JSON/machine-readable output:

Select the tool based on availability (`command -v`), not exit codes — linters exit non-zero when issues are found, which is a valid result to capture.

```bash
# JS/TS — select by availability
if command -v eslint >/dev/null 2>&1; then
  eslint . --format=json 2>/dev/null
elif command -v biome >/dev/null 2>&1; then
  biome check . --reporter=json 2>/dev/null
fi

# Python — prefer Ruff, fall back to flake8
if command -v ruff >/dev/null 2>&1; then
  ruff check . --output-format=json 2>/dev/null
elif command -v flake8 >/dev/null 2>&1; then
  flake8 . --format=json 2>/dev/null
fi

# Go
command -v golangci-lint >/dev/null 2>&1 && golangci-lint run --out-format=json 2>/dev/null

# Rust
command -v cargo-clippy >/dev/null 2>&1 && cargo clippy --message-format=json 2>/dev/null
```

### Complexity Analysis

```bash
# JS/TS — eslint complexity rule or cr tool
eslint . --rule '{"complexity": ["warn", 10]}' --format=json 2>/dev/null

# Python
radon cc . --json --min=C 2>/dev/null

# General — if no tool available, use Claude analysis
# Look for functions > 50 lines, cyclomatic complexity > 10, deep nesting > 4 levels
```

### Duplication Detection

```bash
# JS/TS
jscpd . --reporters=json 2>/dev/null

# General
# If no tool available, Claude analysis: search for repeated code blocks > 10 lines
```

### Dead Code Detection

```bash
# JS/TS — select by availability
if command -v knip >/dev/null 2>&1; then
  knip --reporter=json 2>/dev/null
elif command -v ts-prune >/dev/null 2>&1; then
  ts-prune 2>/dev/null
fi

# Python
command -v vulture >/dev/null 2>&1 && vulture . 2>/dev/null
```

If **no dedicated quality tools are available**, use the Explore agent to discover code quality hotspots across the codebase. Use repomix-explorer (if available) for large codebases to get a structural overview. Then use targeted Grep and Read for detailed analysis:
- Review for unused imports, exports, and functions
- Check for unreachable code paths
- Identify overly complex functions (nesting depth, parameter count)

## Step 3: Classify Findings

Map tool output to the findings format from REPORT-FORMAT.md.

**Severity mapping** (reinforced here for defense-in-depth):

| Finding Type | Severity |
|-------------|----------|
| Error-level lint violation | **High** |
| Cyclomatic complexity > 20 | **High** |
| Warning-level lint violation | **Medium** |
| Cyclomatic complexity 10-20 | **Medium** |
| Duplication > 50 lines | **Medium** |
| Dead code / unused exports | **Low** |
| Style/formatting issues | **Info** |

## Step 4: Create GitHub Issue

**Read [../dlc/references/ISSUE-TEMPLATE.md](../dlc/references/ISSUE-TEMPLATE.md) now** and format the issue body exactly as specified.

**Critical format rules** (reinforced here):
- Title: `[DLC] Quality: {summary of top finding}`
- Label: `dlc-quality`
- Body must contain: Scan Metadata table, Findings Summary table (severity x count), Findings Detail grouped by severity, Recommended Actions, Raw Output in collapsed details

Acquire `BRANCH` for the Scan Metadata table above — ISSUE-TEMPLATE.md's lifecycle acquires `REPO` itself. Then follow ISSUE-TEMPLATE.md's **Issue Creation Command** lifecycle exactly — substitute `{skill-name}` = `quality`, `{Type}` = `Quality`, `{type}` = `quality`, `{additional-required-sections}` = `'## Raw Output'`:

```bash
BRANCH=$(git branch --show-current)
echo "BRANCH=$BRANCH"   # ISSUE-TEMPLATE.md's Write step is a separate tool call and can't see this shell's variables
```

## Step 5: Report

```text
Quality check complete.
  - Linter: {detected linter}
  - Tools used: {list}
  - Findings: {high} high, {medium} medium, {low} low
  - Issue: #{number} ({url})
```

If no findings, skip issue creation and report: "No quality issues found."