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Agent skill

Bloat Detector

by athola in athola/claude-night-market

Detects codebase bloat via dead code, duplication, complexity, and doc bloat scans.

MITAuto-check passedDevelopment

Install Bloat Detector

skills CLI
$ npx skills add athola/claude-night-market --skill bloat-detector -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install athola/claude-night-market bloat-detector --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/athola/claude-night-market.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/conserve/skills/bloat-detector .claude/skills/bloat-detector && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
bloat-detector
GitHub stars
341
Token cost
~1.5k tokens
SKILL.md length
585 words
Files
9
Skills in repo
154
Repo updated
First seen
Licence
MIT

At a glance

Detects codebase bloat via dead code, duplication, complexity, and doc bloat scans.

  • Codebase feels large
  • SKILL.md covers Bloat Categories, Quick Start, When To Use and When NOT To Use, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Before a release

What it does

Bloat Detector is an agent skill from athola/claude-night-market. Detects codebase bloat via dead code, duplication, complexity, and doc bloat scans. Use when codebase feels large or before a release.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files (for example `modules/ai-generated-bloat.md`, `modules/code-bloat-patterns.md` and `modules/documentation-bloat.md`).

It sits in Development. The repository describes itself as: 23 Claude Code plugins: TDD enforcement hooks, git/PR workflows, spec-driven development, code review, project lifecycle, fix-from-error, maintenance automation, context… The licence is MIT.

When your agent uses it

  • Codebase feels large
  • Before a release

Example prompts

  • “Use the bloat-detector skill to detect codebase bloat via dead code, duplication, complexity, and doc bloat scans”
  • “/bloat-detector”

What it can do on your machine

Read from SKILL.md and the folder at commit 9f3eb00. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bloat Detector loads about 1.5k tokens when it runs. Until then it costs about 37 tokens; SKILL.md has 585 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~37
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from athola/claude-night-market at commit 9f3eb00, republished under its MIT licence (© athola). 585 words, ~1,519 tokens.

Download SKILL.mdSave it as .claude/skills/bloat-detector/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
bloat-detector
description
Detects codebase bloat via dead code, duplication, complexity, and doc bloat scans. Use when codebase feels large or before a release.
alwaysApply
false
category
conservation
tags
bloat, cleanup, static-analysis, technical-debt, optimization
modules
modules/quick-scan.md, modules/git-history-analysis.md, modules/growth-analysis.md, modules/code-bloat-patterns.md, modules/ai-generated-bloat.md…
progressive_loading
true
estimated_tokens
400
usage_patterns
bloat, dead code, unused, cleanup, unbloat, prune
model_hint
standard

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)

When NOT To Use

  • Active feature development
  • Time-sensitive bugs
  • Codebase < 1000 lines

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):

  • See modules/quick-scan.md - Heuristics, no tools
  • See modules/git-history-analysis.md - Staleness, churn, vibe coding signatures
  • See modules/growth-analysis.md - Growth velocity, forecasts, threshold alerts

Tier 2 (optional tools):

  • See modules/code-bloat-patterns.md - Anti-patterns (God class, Lava flow)
  • See modules/ai-generated-bloat.md - AI-specific patterns (Tab bloat, hallucinations)
  • See modules/documentation-bloat.md - Redundancy, readability, slop detection
  • See modules/static-analysis-integration.md - Vulture, Knip

Shared:

  • See modules/remediation-types.md - DELETE, REFACTOR, CONSOLIDATE, ARCHIVE

Ecosystem-Level Detection

Patterns that span plugin boundaries or manifest configuration, discovered through ecosystem-wide audits.

alwaysApply Accumulation

Flag plugins with 3+ skills where alwaysApply: true. Each always-on skill injects its full text into every session, creating a baseline token floor before the user types anything. Sum the estimated_tokens fields to report total per-session cost.

Hook Registration Gaps

Compare hooks declared in plugin.json or openpackage.yml against entries in hooks.json. A hook present in hooks.json but absent from the manifest is invisible to the plugin loader and cannot be audited, versioned, or disabled through normal plugin management.

Scan skill files for identical multi-line text blocks repeated across 10+ files (e.g., generic troubleshooting sections like "Command not found / Permission errors / Unexpected behavior"). These are copy-paste artifacts that inflate token cost without adding skill-specific value.

Show full SKILL.md (229 more words)Show less
ToC Bloat in Skills

Skills loaded into model context gain nothing from HTML-style Tables of Contents. Detect ## Table of Contents followed by bulleted anchor-link lists. These waste tokens since the model reads sequentially, not via hyperlinks.

Unregistered Module Subdirectories

Compare files on disk in skills/*/modules/ against the modules: list in each skill's SKILL.md frontmatter. Files that exist on disk but are not listed in the manifest are invisible to progressive loading and may be dead weight or missing from the load path.

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
  • /bloat-scan command - User-facing slash command that invokes this skill; there is no separate bloat-scan skill

Exit Criteria

  • At least one tier of scan (Tier 1, 2, or 3) completed and findings listed per bloat category (Code, AI-Generated, Documentation, Dependencies, Git History)
  • Each finding assigned a confidence level (HIGH/MEDIUM/LOW) and a priority score computed from the formula `(Token_Savings × 0.4) + (Maintenance × 0.3) + (Confidence × 0.2)
    • (Ease × 0.1)`
  • No auto-deletions executed without explicit user approval; every proposed removal documented as DELETE, REFACTOR, CONSOLIDATE, or ARCHIVE per modules/remediation-types.md
  • Ecosystem-level patterns checked (alwaysApply accumulation, hook registration gaps, boilerplate footers, ToC bloat) if the scan target contains plugin directories

© athola, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files in plugins/conserve/skills/bloat-detector of athola/claude-night-market.

  • SKILL.md
  • modules/ai-generated-bloat.md
  • modules/code-bloat-patterns.md
  • modules/documentation-bloat.md
  • modules/git-history-analysis.md
  • modules/growth-analysis.md
  • modules/quick-scan.md
  • modules/remediation-types.md
  • modules/static-analysis-integration.md

Open the folder on GitHubat commit 9f3eb00

Compare with similar skills

Bloat Detector next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Bloat Detector compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Bloat Detector this skillathola/claude-night-market341—~1.5kAutomated safety check: PassMIT
Vercel Composition Patternssupabase/supabase111k58 repos~726Automated safety check: PassMIT
Finishing a Development Branchobra/superpowers297k5 repos~1.9kAutomated safety check: PassMIT
Typescript Advanced Typesrolling-scopes/rsschool-app10k25 repos~4.2kAutomated safety check: PassMPL-2.0
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT

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Categories

Questions about Bloat Detector

What does Bloat Detector do?

Detects codebase bloat via dead code, duplication, complexity, and doc bloat scans. Bloat Detector is an agent skill from athola/claude-night-market. Detects codebase bloat via dead code, duplication, complexity, and doc bloat scans.

When should I use Bloat Detector?

Bloat Detector fits situations like: codebase feels large; before a release.

How do I install Bloat Detector in Claude Code?

Run `npx skills add athola/claude-night-market --skill bloat-detector -a claude-code`. Or copy the skill folder (plugins/conserve/skills/bloat-detector in athola/claude-night-market) into .claude/skills/bloat-detector in your project. Claude Code loads it when a task matches its description.

How do I install Bloat Detector in Codex?

Run `npx skills add athola/claude-night-market --skill bloat-detector -a codex`. Or copy the skill folder (plugins/conserve/skills/bloat-detector in athola/claude-night-market) into .agents/skills/bloat-detector in your project. Codex loads it when a task matches its description.

Can I use Bloat Detector in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add athola/claude-night-market --skill bloat-detector -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bloat-detector, .gemini/skills/bloat-detector, .github/skills/bloat-detector and .opencode/skills/bloat-detector in your project.

What does Bloat Detector need to run?

SKILL.md names no scripts, command-line tools or credentials: Bloat Detector is instructions for the agent only.

Does Bloat Detector access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Bloat Detector safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Bloat Detector use?

Bloat Detector is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Bloat Detector use?

About 1.5k tokens (SKILL.md is roughly 6.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Bloat Detector?

Skills that share tags, products or a category with Bloat Detector: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 297k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and PR Babysitter (openinterpreter/openinterpreter, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bloat Detector?

athola (a GitHub user) maintains it in athola/claude-night-market, which has 341 GitHub stars. The repository holds 154 skills in this directory. The repository was last updated on October 6, 2026.

Source: athola/claude-night-market on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.