askill
bloat-detector

bloat-detectorSafety 95Repository

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

0 stars
1.2k downloads
Updated 2/15/2026

Package Files

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SKILL.md

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

Related

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

Install

Download ZIP
Requires askill CLI v1.0+

AI Quality Score

85/100Analyzed 2/19/2026

Well-structured bloat detection skill with clear tiers, comprehensive categories, and strong safety considerations. Provides actionable progressive analysis with good metadata and clear use cases. Slightly penalized for deep path nesting but content is broadly reusable.

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Metadata

Licenseunknown
Version-
Updated2/15/2026
PublisherVen0m0

Tags

ci-cdobservability