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 mrzhangguoguo/oh-my-workbuddy --skill ai-slop-cleanergit clone --depth 1 https://github.com/mrzhangguoguo/oh-my-workbuddyWrote 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/mrzhangguoguo/oh-my-workbuddy/ai-slop-cleaner)<a href="https://agentmods.dev/skills/mrzhangguoguo/oh-my-workbuddy/ai-slop-cleaner"><img src="https://agentmods.dev/badge/skills/mrzhangguoguo/oh-my-workbuddy/ai-slop-cleaner/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/mrzhangguoguo/oh-my-workbuddy/ai-slop-cleaner"><img src="https://agentmods.dev/badge/skills/mrzhangguoguo/oh-my-workbuddy/ai-slop-cleaner.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 | $0.00066 | $0.01890 |
| Opus 5.5 | $0.00026 | $0.00756 |
| Sonnet 5.5 | $0.00013 | $0.00378 |
| Haiku 4.5 | $0.00007 | $0.00189 |
Grade A, and why
ai-slop-cleaner scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ported from oh-my-codex
ai-slop-cleaner. OMX runtime conventions ($macroinvocation,omxCLI,.omx/state directory) are replaced with WorkBuddy idioms (Skill tool, Agent tool, task list,.workbuddy/memory).
AI Slop Cleaner Skill
Reduce AI-generated slop with a regression-tests-first, smell-by-smell cleanup workflow that preserves behavior and raises signal quality.
When to Use
Use this skill when:
- A code path works but feels bloated, noisy, repetitive, or over-abstracted
- A user asks to "cleanup", "refactor", or "deslop" AI-generated output
- Follow-up implementation left duplicate code, dead code, weak boundaries, missing tests, fallback-like code, or unnecessary wrapper layers
- You need a disciplined cleanup workflow without broad rewrites
Workflow Guidance Alignment
- Keep outputs concise and evidence-dense unless risk or the user requests more detail.
- Treat newer user instructions as local workflow updates without discarding earlier non-conflicting constraints.
- Keep using inspection, tests, diagnostics, and verification until the cleanup is grounded.
- Proceed automatically through clear, reversible cleanup steps; ask only when a choice materially changes scope or behavior.
Scoped File Lists
- This skill can accept a file list scope instead of a whole feature area.
- When the caller provides a changed-files list, keep the cleanup strictly bounded to those files.
- When invoked as a mandatory deslop pass after a coding run, run on the changed files only, in standard mode unless the caller requests otherwise.
Procedure
-
Lock behavior with regression tests first
- Identify the behavior that must not change.
- Add or run targeted regression tests before editing cleanup candidates.
- If behavior is currently untested, create the narrowest test coverage needed first.
- For fallback-like code, cover the primary path and any preserved compatibility/fail-safe fallback before cleanup.
-
Create a cleanup plan before code
- List the specific smells to remove.
- Bound the pass to the requested files/scope.
- Include fallback findings, classifications, and escalation status in the plan.
- Order fixes from safest/highest-signal to riskiest.
- Do not start coding until the cleanup plan is explicit. Track the plan with the task list (TaskCreate/TaskUpdate).
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.
- 1mo ago First seen · 147 lines · 66 tokens per session scan A ffb5d49996e5
ai-slop-cleaner is a skill published in the GitHub repository mrzhangguoguo/oh-my-workbuddy (2 stars, last pushed 3mo ago), licensed MIT. It adds 66 tokens to every session and 1,890 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.
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