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 ao92265/claude-code-playbook --skill anti-ai-prosegit clone --depth 1 https://github.com/ao92265/claude-code-playbookWrote 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/ao92265/claude-code-playbook/anti-ai-prose)<a href="https://agentmods.dev/skills/ao92265/claude-code-playbook/anti-ai-prose"><img src="https://agentmods.dev/badge/skills/ao92265/claude-code-playbook/anti-ai-prose/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/ao92265/claude-code-playbook/anti-ai-prose"><img src="https://agentmods.dev/badge/skills/ao92265/claude-code-playbook/anti-ai-prose.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 | $0.00089 | $0.03096 |
| Opus 5 | $0.00044 | $0.01548 |
| Sonnet 5 | $0.00018 | $0.00619 |
| Haiku 4.5 | $0.00009 | $0.00310 |
Grade A, and why
anti-ai-prose 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 11d 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Anti-AI Prose
Default LLM writing has a smell. This skill kills it.
The problem with rule-based de-AI-ing
A clean, balanced, well-structured paragraph is itself a tell. Real people write asymmetrically. They run sentences together, drop subjects, use "it" with no antecedent, swear when annoyed, abandon a thought mid-line.
Rules to delete AI tells aren't enough. You also have to write like a person who's tired and slightly pissed off.
Banned patterns (AI fingerprints)
Structural
- Em-dash mid-sentence flourishes. ("Claude is great — but it's a black box.") → split into two sentences.
- Parallel triplets / quads. ("Sub-agents fork off, hooks fire, MCP servers chew tokens.") → pick the strongest one. Cut the rest.
- Numbered/comma-separated lists inside a sentence when prose would do.
- Signposting. "First...", "Second...", "Finally...", "In summary..." Humans don't number paragraphs.
- "It's not just X, it's Y" / "Whether you're A or B, this is C" constructions.
- Bold every 3rd noun.
- Section headers for a single paragraph.
Openers
"Hey all", "Hey team", "So here's the thing", "I wanted to share", "Let me tell you", "I've been thinking about", "Picture this", rhetorical questions.
Vocabulary
- Hype: amazing, powerful, transformative, game-changing, revolutionize, unlock, supercharge, seamless, robust, leverage, utilize, dive deep, comprehensive, holistic, paradigm, journey.
- Hedge: you should, try to, generally, usually, typically, where appropriate, if possible, it's worth noting.
- Filler: at the end of the day, in today's fast-paced world, in the rapidly evolving landscape.
- OSS-template: "Issues and PRs welcome", "Contributions appreciated", "Star if you find it useful", "Star history".
Closers
"I hope this helps", "Let me know if you have any questions", "Looking forward to your thoughts", "Cheers!", "Stay tuned", "Until next time".
Register-neutral tells (detection pass)
The patterns above target casual voice. These fire in any register — casual and formal (Viva, blog, professional). Run this pass before the casual rewrite; on formal drafts where lowercase/profanity don't apply, this pass is the whole job. Each is detect → fix.
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.
- 11d ago First seen · 188 lines · 89 tokens per session scan A 744226034900
anti-ai-prose is a skill published in the GitHub repository ao92265/claude-code-playbook (10 stars, last pushed today), licensed MIT. It adds 89 tokens to every session and 3,096 once invoked, about $0.0004 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…