slop-cleaner

slop-cleaner is a cursor rule for Cursor from dasomel/oh-my-cursor. It costs 19 tokens per session (523 once invoked), scanned A, original, MIT.

A code-cleanup workflow for removing unnecessary AI-generated code, such as dead code, needless wrappers, excessive comments, and overcomplicated error handling.

In plain words
What is it for?
Use it to test the current code, find unnecessary parts, delete them one at a time, and keep only deletions that leave the tests passing.
Why use it?
It reduces clutter while using tests to check that deleting each questionable part does not change the existing behaviour.

Cursor rule for Cursor

Written for Cursor: a Cursor rule (.mdc).

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 rules/dasomel/oh-my-cursor/slop-cleaner
Clone the repo
git clone --depth 1 https://github.com/dasomel/oh-my-cursor

Made for: Cursor.

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 slop-cleaner

README.md
[![agentmods](https://agentmods.dev/badge/rules/dasomel/oh-my-cursor/slop-cleaner.svg)](https://agentmods.dev/rules/dasomel/oh-my-cursor/slop-cleaner)
Your own site
<a href="https://agentmods.dev/rules/dasomel/oh-my-cursor/slop-cleaner"><img src="https://agentmods.dev/badge/rules/dasomel/oh-my-cursor/slop-cleaner.svg" alt="Measured on agentmods" height="20"></a>
Per session 19 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 523 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 $0.00019 $0.00523
Opus 5 $0.00010 $0.00262
Sonnet 5 $0.00004 $0.00105
Haiku 4.5 $0.00002 $0.00052

Measured 6d ago against content hash bc64661e55d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

slop-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 6d 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.

rules/workflows/slop-cleaner.mdc · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Slop Cleaner Workflow

Clean AI-generated code slop — test first, then delete aggressively.

Trigger Keywords

"deslop", "clean slop", "anti-slop", "AI generated cleanup"

What is "Slop"?

AI-generated code that works but has quality issues:

  • Unnecessary abstractions (wrapper functions used once)
  • Over-defensive error handling (checking impossible states)
  • Verbose comments explaining obvious code
  • Feature flags and backward-compatibility shims for nothing
  • Premature optimization or generalization
  • Copy-pasted patterns that should be unified

Process

Phase 1: TEST BASELINE
  [Test Engineer] → Ensure existing tests pass
  [Test Engineer] → Add missing tests for current behavior
  → Tests are our safety net for deletion

Phase 2: IDENTIFY SLOP
  [Code Simplifier] → Scan for slop patterns:
    - Dead code, unused exports, unreachable branches
    - Single-use abstractions
    - Comments that restate the code
    - Over-engineered error handling
    - Unnecessary type assertions

Phase 3: DELETE (not refactor!)
  [Executor] → For each slop item:
    1. Delete it
    2. Run tests
    3. If tests pass → keep deletion
    4. If tests fail → undo, investigate, then fix properly

Phase 4: VERIFY
  [Verifier] → Full test suite, build, type check
  [Reviewer] → Quick review of changes

Deletion Priorities

Priority Target Action
1 Dead code Delete entirely
2 Obvious comments Delete (// increment i above i++)
3 Single-use wrappers Inline the code
4 Unnecessary try/catch Remove if error can't happen
5 Premature abstractions Flatten to direct code

Rules

  • Delete before refactoring — simpler is always better
  • Tests first — never delete without test coverage
  • One deletion at a time — commit after each successful deletion
  • Preserve behavior — slop cleaning changes style, never logic
  • Announce: "Starting Slop Cleaner — establishing test baseline first."

Read the full file on GitHub · 69 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. 6d ago First seen · 69 lines · 19 tokens per session scan A bc64661e55d8

Subscribe to this mod's changes

slop-cleaner is a cursor rule published in the GitHub repository dasomel/oh-my-cursor (2 stars, last pushed 6mo ago), licensed MIT. It adds 19 tokens to every session and 523 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.