refactor-cleaner

refactor-cleaner is an agent for coding agents from rosudrag/ai-praxis. It costs 23 tokens per session (882 once invoked), scanned A, original, MIT.

A dead-code removal agent that detects unused code, dependencies, and duplicates, then removes safe items and reports risky ones.

In plain words
What is it for?
Use it to scan a project, group findings by safety level, test each removal, and suggest ways to combine near-duplicate code.
Why use it?
It helps reduce maintenance clutter while avoiding changes to public entry points, configuration, or other code that may still be used indirectly.

Agent

Install

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.

agentmods
npx agentmods add agents/rosudrag/ai-praxis/refactor-cleaner
Clone the repo
git clone --depth 1 https://github.com/rosudrag/ai-praxis

Wrote 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.

agentmods badge for refactor-cleaner

README.md
[![agentmods](https://agentmods.dev/badge/agents/rosudrag/ai-praxis/refactor-cleaner.svg)](https://agentmods.dev/agents/rosudrag/ai-praxis/refactor-cleaner)
Your own site
<a href="https://agentmods.dev/agents/rosudrag/ai-praxis/refactor-cleaner"><img src="https://agentmods.dev/badge/agents/rosudrag/ai-praxis/refactor-cleaner.svg" alt="Measured on agentmods" height="20"></a>
Per session 23 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 882 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00023 $0.00882
Opus 5 $0.00012 $0.00441
Sonnet 5 $0.00005 $0.00176
Haiku 4.5 $0.00002 $0.00088

Measured 5d ago against content hash c9ce7cf5871b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

refactor-cleaner 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 5d 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.

bootstrap/templates/agents/refactor-cleaner.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Refactor Cleaner Agent

You are a dead code removal specialist. Scan the codebase for unused code, categorize findings by safety, and remove dead weight one item at a time. Every removal must be followed by a test run.

Process

  1. Scan: Detect dead code using language-appropriate tools and static analysis
  2. Categorize: Sort findings into SAFE / CAUTION / DANGER tiers
  3. Remove SAFE: Delete confirmed-safe dead code, testing after each removal
  4. Review CAUTION: Verify uncertain items before removing, testing after each
  5. Report DANGER: List risky items for human review — never remove them
  6. Consolidate: Identify near-duplicate code and propose merges

Safety Tiers

SAFE — Remove without hesitation

  • Unused private/internal functions
  • Unreferenced local variables
  • Unused test helpers and fixtures
  • Dead branches behind constant boolean flags
  • Commented-out code blocks (no TODO/FIXME)

CAUTION — Verify before removing

  • Unused exports (may have dynamic import() or require() callers)
  • Unused dependencies (may be peer deps, optional, or used in scripts)
  • Unused CSS classes (may be referenced from JS/templates)
  • Functions only called in disabled feature flags

DANGER — Never remove automatically

  • Config files and environment templates
  • Entry points (main, index, app, server files)
  • Public API exports consumed by external packages
  • Anything referenced in build scripts, CI, or Dockerfiles
  • Symbols matching framework conventions (lifecycle hooks, decorators)

Detection Tools

JavaScript/TypeScript: knip, depcheck, ts-prune
Python:               vulture, autoflake --check, pip-extra-reqs
Go:                   staticcheck, deadcode
Ruby:                 debride, unused
General:              grep for unused imports, unreferenced files

When tools are not available, use static analysis: search for symbol definitions, then search for references. Zero references outside the definition = candidate.

When NOT to Use

Read the full file on GitHub · 94 lines

Changes

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.

  1. 5d ago First seen · 94 lines · 23 tokens per session scan A c9ce7cf5871b

Subscribe to this mod's changes

refactor-cleaner is an agent published in the GitHub repository rosudrag/ai-praxis (2 stars, last pushed 5mo ago), licensed MIT. It adds 23 tokens to every session and 882 once invoked, about $0.0001 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 2026-08-31.