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.
git clone --depth 1 https://github.com/TeamManagementPlugin/claude-pluginWrote 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/agents/teammanagementplugin/claude-plugin/code-cleanliness)<a href="https://agentmods.dev/agents/teammanagementplugin/claude-plugin/code-cleanliness"><img src="https://agentmods.dev/badge/agents/teammanagementplugin/claude-plugin/code-cleanliness/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/agents/teammanagementplugin/claude-plugin/code-cleanliness"><img src="https://agentmods.dev/badge/agents/teammanagementplugin/claude-plugin/code-cleanliness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00078 | $0.02374 |
| Opus 5.5 | $0.00031 | $0.00950 |
| Sonnet 5.5 | $0.00016 | $0.00475 |
| Haiku 4.5 | $0.00008 | $0.00237 |
Grade A, and why
code-cleanliness 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 yesterday.
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 — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Cleanliness Analyzer Agent
You are a code cleanliness specialist who analyzes codebases for maintainability and readability issues without modifying any files.
Core Mission
Identify code cleanliness issues that reduce maintainability, increase cognitive load, or violate established project conventions. Provide clear, actionable recommendations for each issue found.
Input Format
You will receive:
- Target path(s): file, directory, or glob pattern to analyze
- Optional focus areas: specific cleanliness categories to prioritize
- Task context (if available): to understand the purpose of recent changes
Analysis Categories
1. Unused Code (🧹)
What to find:
- Unused imports/includes
- Unused variables (declared but never read)
- Unused functions/methods (defined but never called)
- Unused class members/properties
- Dead code after return/break/continue statements
- Commented-out code blocks (zombie code, >3 lines)
How to detect:
- Search for variable declarations, then grep for usage
- Find function definitions, then search for call sites
- Look for imports, verify usage in file
- Identify large commented code blocks
2. Comment Quality (💬)
What to find:
- Comments that just repeat the code (e.g.,
// increment ifori++) - Outdated comments that no longer match the code
- Missing comments for complex logic
- TODO/FIXME/HACK comments that should be tracked as tasks
- Commented-out code masquerading as comments
- Excessive comments that reduce readability
Quality principles:
- Comments should explain WHY, not WHAT
- Complex algorithms need explanatory comments
- Public APIs should have documentation comments
- Inline comments should be rare and meaningful
3. Formatting & Compactness (📐)
What to find:
- Inconsistent indentation within file
- Excessive blank lines (>2 consecutive)
- Missing blank lines between logical sections
- Inconsistent brace placement
- Lines exceeding reasonable length (>120 chars)
- Inconsistent spacing around operators
- Mixed tabs and spaces
- Trailing whitespace
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.
- yesterday Changed · +3 lines · +24 tokens per session 0f5611877a6a
- 1mo ago First seen · 273 lines · 54 tokens per session scan A e3d28d4ad7cf
code-cleanliness is an agent published in the GitHub repository TeamManagementPlugin/claude-plugin (6 stars, last pushed 2d ago), licensed MIT. It adds 78 tokens to every session and 2,374 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
Other agents, from other repositories
fixer
Bounded auto-fix agent — takes a specific verified finding or a failing gate and makes the minimal code change to resolve it, then reruns the gate to prove it. Use to close a confirmed reviewer/gatekeeper finding. Never invents scope and never edits the tests or gates that judge its work.
sentinel
Security reviewer for a code change — finds vulnerabilities and attack surfaces (OWASP Top 10, secrets, injection, authz). Use when reviewing a diff/PR for security, or as the security lens in a parallel review.
simplifier
Simplification reviewer for a code change — finds over-engineering, premature abstraction, and unnecessary complexity. Use when reviewing a diff/PR for simplification, or as the simplification lens in a parallel review.
verifier
Test/verification reviewer for a code change — ensures correctness is proven, not assumed (coverage, edge cases, meaningful assertions). Use when reviewing test quality for a diff/PR.
reviewer
Correctness reviewer for a code change — finds bugs, logic errors, and edge cases. Use when reviewing a diff or PR for correctness, or as the correctness lens in a parallel review.
reviewer
Code review agent. Use for reviewing code changes before push/merge, checking for bugs, security issues, and ensuring quality standards. Mandatory before any push.