Linting Codebase

Overview

This skill runs lint checks on the codebase, analyzes the results to identify independent fix streams, and dispatches parallel AI agents to fix all issues. The process iterates until the codebase passes all lint checks.

Core principle: Group lint issues by file/component, dispatch one agent per independent stream, iterate until clean.

⛔ CRITICAL CONSTRAINTS

These constraints are NON-NEGOTIABLE and must be communicated to ALL dispatched agents:

┌─────────────────────────────────────────────────────────────────┐
│  🚫 DO NOT CREATE AUTOMATED SCRIPTS TO FIX LINT ISSUES         │
│  🚫 DO NOT CREATE DOCUMENTATION OR README FILES                 │
│  🚫 DO NOT ADD COMMENTS EXPLAINING THE FIXES                   │
│  ✅ FIX EACH ISSUE DIRECTLY BY EDITING THE SOURCE CODE         │
│  ✅ MAKE MINIMAL CHANGES - ONLY WHAT'S NEEDED FOR LINT         │
└─────────────────────────────────────────────────────────────────┘

Phase 1: Lint Execution

Step 1.1: Detect Lint Command

Priority: make lint → npm run lint → yarn lint → pnpm lint → golangci-lint run → cargo clippy → ruff check . → eslint .

Step 1.2: Run Lint

<lint_command> 2>&1 | tee /tmp/lint-output.txt && echo "EXIT_CODE: $?"

Step 1.3: Parse Results

Extract: file path, line:column, error code/rule, message, severity (error/warning).

Phase 2: Stream Analysis

Step 2.1: Group Issues

Group lint issues into independent streams that can be fixed in parallel:

Grouping strategies (choose based on issue count):

Step 2.2: Identify Independence

A stream is independent if: files don't import/depend on each other, fixes won't conflict, agents can work without knowledge of other streams.

Step 2.3: Create Stream Summary

Output format: Total issues, Streams (path, issue types, count, independence status), Recommended agents (one per stream).

Phase 3: Parallel Agent Dispatch

Step 3.1: Prepare Agent Prompts

Each agent receives: Scope (files/directories), Issues (file:line:col + message), Constraints (from Critical Constraints above), Output (files modified, issues fixed, issues unable to fix with reasons).

Step 3.2: Dispatch Agents in Parallel

CRITICAL: Single message with multiple Task tool calls - one general-purpose agent per stream.

Step 3.3: Await All Agents

Wait for all dispatched agents to complete before proceeding.

Phase 4: Verification Loop

Step 4.1: Re-run Lint

After all agents complete, run <lint_command> 2>&1.

Step 4.2: Evaluate Results

Step 4.3: Iterate If Needed

Maximum iterations: 5. If issues persist: report remaining, ask user, investigate (lint conflicts, auto-fix impossible).

Agent Dispatch Rules

DO dispatch when:

• 3+ files have lint issues
• Issues are in independent areas
• Fixes are mechanical (unused vars, formatting, etc.)

DO NOT dispatch when:

• Single file has issues → fix directly
• Issues require architectural decisions
• Fixes would cause breaking changes

Agent selection:

Output Format

Success: Initial issues, Streams processed, Agents dispatched, Iterations, Final status (all pass), Changes by stream (files, issues fixed).

Partial: Initial/fixed/remaining issues, Iterations (max reached), Remaining issues with reasons (e.g., requires external types, intentional usage), Recommended actions (manual review, lint exceptions, type definitions).

Error Handling

Integration with Other Skills

Example Session

/lint → Run lint → 16 issues in 3 areas → Analyze streams (API: 5, Services: 8, Utils: 3) → Dispatch 3 parallel agents → All complete → Re-run lint → ✅ All pass.