Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add athola/claude-night-market --skill bloat-detectorgit clone --depth 1 https://github.com/athola/claude-night-marketWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/athola/claude-night-market/bloat-detector)<a href="https://agentmods.dev/skills/athola/claude-night-market/bloat-detector"><img src="https://agentmods.dev/badge/skills/athola/claude-night-market/bloat-detector/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/athola/claude-night-market/bloat-detector"><img src="https://agentmods.dev/badge/skills/athola/claude-night-market/bloat-detector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00036 | $0.01534 |
| Opus 5 | $0.00018 | $0.00767 |
| Sonnet 5 | $0.00007 | $0.00307 |
| Haiku 4.5 | $0.00004 | $0.00153 |
Grade A, and why
bloat-detector scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bloat Detector
Systematically detect and eliminate codebase bloat through progressive analysis tiers.
Bloat Categories
| Category | Examples |
|---|---|
| Code | Dead code, God classes, Lava flow, duplication |
| AI-Generated | Tab-completion bloat, vibe coding, hallucinated deps |
| Documentation | Redundancy, verbosity, stale content, slop |
| Dependencies | Unused imports, dependency bloat, phantom packages |
| Git History | Stale 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
| Do | Don't |
|---|---|
| Context usage > 30% | Active feature development |
| Quarterly maintenance | Time-sensitive bugs |
| Pre-release cleanup | Codebase < 1000 lines |
| Before major refactoring | Tools unavailable (Tier 2/3) |
When NOT To Use
- Active feature development
- Time-sensitive bugs
- Codebase < 1000 lines
Confidence Levels
| Level | Confidence | Action |
|---|---|---|
| HIGH | 90-100% | Safe to remove |
| MEDIUM | 70-89% | Review first |
| LOW | 50-69% | 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
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 191 lines · 36 tokens per session scan A d3f4deaa6c0b
bloat-detector is a skill published in the GitHub repository athola/claude-night-market (337 stars, last pushed yesterday), licensed MIT. It adds 36 tokens to every session and 1,534 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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fact-checker
Anti-hallucination discipline for any code that names an external symbol you aren't certain exists — a library function, method, config key, package version, CLI flag, env var, or endpoint. Before you call it, cite it, or import it, confirm it's real: grep the codebase, read the installed package's actual signature…
review-all
Multi-agent code review for diffs (project-agnostic). Covers standards, bugs, security, DRY, smells, perf, tests, API contracts, a11y/i18n. Verifies each finding to eliminate false positives. Use for /review-all, pre-PR/pre-commit review, or auditing uncommitted/staged changes.
find-bugs
Locate likely bug locations in code.
audit-quality-gates
Use this skill when the user wants to audit how a project configures its style checkers and static analyzers.
repoimmune
Query evidence-backed historical bugs before risky code changes and verify patches before completion.
Refactor Engine
Improves existing codebases by restructuring for clarity, performance, and maintainability without changing external behavior.