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 opencue/cuecards --skill ai-slop-detectorgit clone --depth 1 https://github.com/opencue/cuecardsWrote 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/opencue/cuecards/ai-slop-detector)<a href="https://agentmods.dev/skills/opencue/cuecards/ai-slop-detector"><img src="https://agentmods.dev/badge/skills/opencue/cuecards/ai-slop-detector/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/opencue/cuecards/ai-slop-detector"><img src="https://agentmods.dev/badge/skills/opencue/cuecards/ai-slop-detector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.03528 |
| Opus 5 | $0.00021 | $0.01764 |
| Sonnet 5 | $0.00008 | $0.00706 |
| Haiku 4.5 | $0.00004 | $0.00353 |
Grade A, and why
ai-slop-detector 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 9d 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 — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
slop-cop
A universal prose audit with two parallel axes. Built on ~135 published sources spanning peer-reviewed linguistics, AI-detector vendor methodology, plain-language style guides (plainlanguage.gov, GOV.UK, Microsoft, Google), cognitive-load research (Miller, Sweller, Pinker), web-readability research (NN/g), and the Plain Writing Act / WCAG accessibility standards.
The one-line summary
Two axes, two verdicts. AI-Slop and Comprehension. A piece can pass one and fail the other.
- AI-Slop axis, Does this read like AI wrote it? Patterns, vocabulary, formatting, rhythm.
- Comprehension axis, Can a fresh reader follow this? Acronyms, named-entity bombing, telegraphic compression, readability, structure.
Single instances aren't a signal. Density is. Both axes use density-based scoring (per 500 words, weighted by severity) with the same verdict tiers (PASS / LOW / MEDIUM / HIGH / CRITICAL). The audit reports both and combines them into a single recommendation based on whichever is worse.
Why this skill exists
Our feeds are becoming shit. Our websites are becoming shit. Our repos are becoming shit. AI didn't make writing harder, it made writing easier, and now everyone uses the same shortcuts, the same shapes, the same words. Open ten landing pages in a row and you can't tell them apart.
I built this skill to make my own websites less shit, my clients' websites less shit, and my LinkedIn feed less of a copy-paste graveyard. Yes, AI wrote parts of this skill. That is not the problem. The problem is AI prose nobody catches: the safe, hedge-stacked, em-dash-heavy paragraph where every line is grammatically clean but the whole thing is forgettable.
I run this against my own work every day. Landing pages, blog posts, READMEs, pitch decks, cold emails. It catches the stuff I would have shipped. If someone uses it to score other people's writing, fine. The first job is policing yourself before you ship.
Running it daily means finding new things every week. A pattern I missed. A false alarm on real human prose. A new model with new tells. The list moves with the work. Expect a lot of changes.
What ships with it
13 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- banner.svg 1.3 KB
- LICENSE 1.0 KB
- README.md 5.0 KB
- references/audit-report-template.md 9.8 KB
- references/calibration.md 24 KB
- references/comprehension.md 28 KB
- references/cop_slop_1.9.zip 456 KB
- references/formatting-tells.md 12 KB
- references/patterns.md 55 KB
- references/readability-metrics.md 12 KB
- references/sources.md 30 KB
- references/vocabulary.md 15 KB
- scripts/scan.py 107 KB runs code
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.
- 9d ago First seen · 279 lines · 42 tokens per session scan A 2231a4fc7b97
ai-slop-detector is a skill published in the GitHub repository opencue/cuecards (5 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 3,528 once invoked, about $0.0002 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.
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