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athola

bloat-detector

by athola

Marketplace repo for Claude Code Plugins developed from personal projects and workflow

127🍴 16📅 Jan 23, 2026

SKILL.md


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)

/bloat-scan

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

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

/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)

/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

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

Score

Total Score

70/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

+10
説明文

100文字以上の説明がある

0/10
人気

GitHub Stars 100以上

+5
最近の活動

1ヶ月以内に更新

+10
フォーク

10回以上フォークされている

+5
Issue管理

オープンIssueが50未満

0/5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

+5

Reviews

💬

Reviews coming soon