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 mike-coulbourn/claude-vibes --skill ai-writing-detectiongit clone --depth 1 https://github.com/mike-coulbourn/claude-vibesWrote 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/mike-coulbourn/claude-vibes/ai-writing-detection)<a href="https://agentmods.dev/skills/mike-coulbourn/claude-vibes/ai-writing-detection"><img src="https://agentmods.dev/badge/skills/mike-coulbourn/claude-vibes/ai-writing-detection/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/mike-coulbourn/claude-vibes/ai-writing-detection"><img src="https://agentmods.dev/badge/skills/mike-coulbourn/claude-vibes/ai-writing-detection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk 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 | $0.00044 | $0.02274 |
| Opus 5 | $0.00022 | $0.01137 |
| Sonnet 5 | $0.00009 | $0.00455 |
| Haiku 4.5 | $0.00004 | $0.00227 |
Grade A, and why
ai-writing-detection 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.
This is a copy
100% identical to ai-writing-detection — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Writing Detection Reference
Expert-level knowledge base for detecting AI-generated text, compiled from academic research, commercial detection tools, and empirical analysis.
Quick Reference: High-Confidence Signals
These indicators strongly suggest AI authorship when found together:
Vocabulary Red Flags
High-signal words (50-700x more common in AI text):
- "delve", "tapestry", "nuanced", "multifaceted", "underscore"
- "intricate interplay", "played a crucial role", "complex and multifaceted"
- "paramount", "pivotal", "meticulous", "holistic", "robust"
- "stands/serves as", "marking a pivotal moment", "underscores its importance"
Overused phrases:
- "It's important to note that..."
- "In today's fast-paced world..."
- "At its core..."
- "Without further ado..."
- "Let me explain..."
See reference/vocabulary-patterns.md for complete lists.
Structural Red Flags
- Uniform sentence lengths: 12-18 words consistently (low burstiness)
- Tricolon structures: "research, collaboration, and problem-solving"
- Em dash overuse: AI uses em dashes in a formulaic way to mimic "punched up" sales writing, especially in parallelisms ("it's not X — it's Y"); swapping punctuation doesn't fix the underlying emphasis pattern
- Perfect paragraph uniformity: All paragraphs same approximate length
- Template conclusions: "In summary...", "In conclusion..."
- Negative parallelisms: "It's not about X; it's about Y"
- Elegant variation: Cycling through synonyms to avoid repetition
- False ranges: "From X to Y" with incoherent endpoints
See reference/structural-patterns.md for details.
Content Red Flags
- Importance puffery: "marking a pivotal moment in history"
- Ecosystem/conservation claims without citations
- "Challenges and Future" sections following rigid formula
- Promotional language: "nestled in", "stunning natural beauty", "boasts"
- Superficial analyses: "-ing" phrases attributing significance to facts
What ships with it
8 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.
- reference/citation-patterns.md 8.1 KB
- reference/content-patterns.md 8.1 KB
- reference/false-positive-prevention.md 13 KB
- reference/formatting-patterns.md 7.2 KB
- reference/markup-artifacts.md 8.6 KB
- reference/model-fingerprints.md 8.3 KB
- reference/structural-patterns.md 14 KB
- reference/vocabulary-patterns.md 7.5 KB
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 · 237 lines · 44 tokens per session scan A 080b6fba7844
ai-writing-detection is a skill published in the GitHub repository mike-coulbourn/claude-vibes (39 stars, last pushed 8mo ago), licensed MIT. It adds 44 tokens to every session and 2,274 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to ai-writing-detection, differing in 0 lines, and is treated as a copy.
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