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 agentmods add skills/bobbyjohnstx/tinycode/ai-slop-cleanernpx skills add bobbyjohnstx/tinycode --skill ai-slop-cleanergit clone --depth 1 https://github.com/bobbyjohnstx/tinycodeWhat 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 | $0.00025 | $0.01390 |
| Opus 5 | $0.00013 | $0.00695 |
| Sonnet 5 | $0.00005 | $0.00278 |
| Haiku 4.5 | $0.00003 | $0.00139 |
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 2d 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Slop Cleaner
Use this skill to clean AI-generated code slop without drifting scope or changing intended behavior. This is the bounded cleanup workflow for code that works but feels bloated, repetitive, weakly tested, or over-abstracted.
When to Use
Use this skill when:
- the user explicitly says
deslop,anti-slop, orAI slop - the request is to clean up or refactor code that feels noisy, repetitive, or overly abstract
- follow-up implementation left duplicate logic, dead code, wrapper layers, boundary leaks, or weak regression coverage
- the user wants a reviewer-only anti-slop pass via
--review - the goal is simplification and cleanup, not new feature delivery
When Not to Use
Do not use this skill when:
- the task is mainly a new feature build or product change
- the user wants a broad redesign instead of an incremental cleanup pass
- the request is a generic refactor with no simplification or anti-slop intent
- behavior is too unclear to protect with tests or a concrete verification plan
Execution Posture
- Preserve behavior unless the user explicitly asks for behavior changes.
- Lock behavior with focused regression tests first whenever practical.
- Write a cleanup plan before editing code.
- Prefer deletion over addition.
- Reuse existing utilities and patterns before introducing new ones.
- Avoid new dependencies unless the user explicitly requests them.
- Keep diffs small, reversible, and smell-focused.
- Stay concise and evidence-dense: inspect, edit, verify, and report.
- Treat new user instructions as local scope updates without dropping earlier non-conflicting constraints.
Scoped File-List Usage
This skill can be bounded to an explicit file list or changed-file scope when the caller already knows the safe cleanup surface.
- Good fit:
/ai-slop-cleaner src/auth/middleware.ts src/auth/utils.ts - Good fit: cleanup scoped to only the files changed in a prior session
- Preserve the same regression-safe workflow even when the scope is a short file list
- Do not silently expand a changed-file scope into broader cleanup work unless the user explicitly asks for it
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.
- 2d ago First seen · 134 lines · 25 tokens per session scan A b933ae414055
ai-slop-cleaner is a skill published in the GitHub repository bobbyjohnstx/tinycode (11 stars, last pushed 5d ago), licensed MIT. It adds 25 tokens to every session and 1,390 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 2026-08-30.
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