AgentSkillsCN

bloat-detector

通过渐进式分析检测代码库的冗余问题：死代码、代码重复、复杂度过高、文档臃肿。 触发条件：冗余检测、死代码、代码清理、代码重复、技术债务、未使用的代码 适用场景：上下文使用率较高、季度性维护、发布前清理、重构前 禁忌场景：活跃功能开发、时间紧迫的 Bug 修复、代码库规模小于 1000 行

SKILL.md
--- frontmatter
name: bloat-detector
description: |
  Detect codebase bloat through progressive analysis: dead code, duplication, complexity, documentation bloat.

  Triggers: bloat detection, dead code, code cleanup, duplication, technical debt, unused code

  Use when: context usage high, quarterly maintenance, pre-release cleanup, before refactoring
  DO NOT use when: active feature development, time-sensitive bugs, codebase < 1000 lines
category: conservation
tags: [bloat, cleanup, static-analysis, technical-debt, optimization]
tools: [Bash, Grep, Glob, Read]
modules:
  - quick-scan
  - git-history-analysis
  - code-bloat-patterns
  - ai-generated-bloat
  - documentation-bloat
  - static-analysis-integration
  - remediation-types
progressive_loading: true
estimated_tokens: 400

Bloat Detector

Systematically detect and eliminate codebase bloat through progressive analysis tiers.

Bloat Categories

CategoryExamples
CodeDead code, God classes, Lava flow, duplication
AI-GeneratedTab-completion bloat, vibe coding, hallucinated deps
DocumentationRedundancy, verbosity, stale content, slop
DependenciesUnused imports, dependency bloat, phantom packages
Git HistoryStale files, low-churn code, massive single commits

Quick Start

Tier 1: Quick Scan (2-5 min, no tools)

bash
/bloat-scan

Detects: Large files, stale code, old TODOs, commented blocks, basic duplication

Tier 2: Targeted Analysis (10-20 min, optional tools)

bash
/bloat-scan --level 2 --focus code   # or docs, deps

Adds: Static analysis (Vulture/Knip), git churn hotspots, doc similarity

Tier 3: Deep Audit (30-60 min, full tooling)

bash
/bloat-scan --level 3 --report audit.md

Adds: Cross-file redundancy, dependency graphs, readability metrics

When to Use

DoDon't
Context usage > 30%Active feature development
Quarterly maintenanceTime-sensitive bugs
Pre-release cleanupCodebase < 1000 lines
Before major refactoringTools unavailable (Tier 2/3)

Confidence Levels

LevelConfidenceAction
HIGH90-100%Safe to remove
MEDIUM70-89%Review first
LOW50-69%Investigate

Prioritization

code
Priority = (Token_Savings × 0.4) + (Maintenance × 0.3) + (Confidence × 0.2) + (Ease × 0.1)

Module Architecture

Tier 1 (always available):

  • •@module:quick-scan - Heuristics, no tools
  • •@module:git-history-analysis - Staleness, churn, vibe coding signatures

Tier 2 (optional tools):

  • •@module:code-bloat-patterns - Anti-patterns (God class, Lava flow)
  • •@module:ai-generated-bloat - AI-specific patterns (Tab bloat, hallucinations)
  • •@module:documentation-bloat - Redundancy, readability, slop detection
  • •@module:static-analysis-integration - Vulture, Knip

Shared:

  • •@module:remediation-types - DELETE, REFACTOR, CONSOLIDATE, ARCHIVE

Auto-Exclusions

Always excludes: .venv, __pycache__, .git, node_modules, dist, build, vendor

Also respects: .gitignore, .bloat-ignore

Safety

  • •Never auto-delete - all changes require approval
  • •Dry-run support - --dry-run for previews
  • •Backup branches - created before bulk changes

Related

  • •bloat-auditor agent - Executes scans
  • •unbloat-remediator agent - Safe remediation
  • •context-optimization skill - MECW principles