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 travsteward/openwriter --skill anti-aigit clone --depth 1 https://github.com/travsteward/openwriterWrote 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/travsteward/openwriter/anti-ai)<a href="https://agentmods.dev/skills/travsteward/openwriter/anti-ai"><img src="https://agentmods.dev/badge/skills/travsteward/openwriter/anti-ai/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/travsteward/openwriter/anti-ai"><img src="https://agentmods.dev/badge/skills/travsteward/openwriter/anti-ai.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 | $0.00135 | $0.01662 |
| Opus 5 | $0.00068 | $0.00831 |
| Sonnet 5 | $0.00027 | $0.00332 |
| Haiku 4.5 | $0.00014 | $0.00166 |
Grade A, and why
anti-ai 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Anti-AI Detection Rules
Two tiers. Tier 1 rules are hard rules — fix unconditionally, no voice profile override. These patterns are so statistically associated with AI that detectors flag them regardless of context. Tier 2 rules are voice-gated — check against the voice profile before fixing.
Tier 1: Hard Rules (Always Fix)
Em-dashes — eliminate, then calibrate. AI uses em-dashes at 5-10x human density. This is one of the strongest AI signals.
- Default (no profile or generic voice): Zero em-dashes. Convert to periods, commas, or parentheses.
- With voice profile: Check the author's samples. If they use em-dashes, match their frequency — never exceed it. An author at 1 per 300 words gets 1 per 300 words. An author who never uses them gets zero.
Contrastive formula — never use. These constructions are AI fingerprints:
- "It's not X, it's Y" / "This isn't X, it's Y"
- "Rather than X, we should Y"
- "Instead of X, consider Y"
- "Not merely X, but Y" Rewrite without the formula. State the point directly.
Nuclear phrases — kill on sight. These phrases are 100-900x more frequent in AI text than human text. No human writes them at this density:
- "valuable insights" (902x) · "indelible mark" (319x) · "rich tapestry" (227x)
- "crucial role in shaping" (250x) · "adds a layer of complexity" (194x)
- "a stark reminder" (151x) · "fostering a sense" (138x) · "nuanced understanding" (115x)
- "unwavering commitment" (256x) · "multifaceted nature" (92x) · "beacon of hope" (58x)
- "delve deeper" (72x) · "navigate the complex" (87x) · "transformative power" (74x)
- "shed light on" · "serves as a testament" · "underscores the importance"
Copula avoidance — use simple verbs. AI replaces "is" with "serves as", "has" with "boasts", "shows" with "underscores." This is a telltale pattern. Use the simple verb.
Sycophantic filler — cut unconditionally. "Interestingly", "It's worth noting", "Notably", "It is important to note that", "It's crucial to understand" — these are AI padding. Delete them. They add nothing.
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 · 102 lines · 135 tokens per session scan A 606f3ad5a46f
anti-ai is a skill published in the GitHub repository travsteward/openwriter (27 stars, last pushed 2d ago), licensed MIT. It adds 135 tokens to every session and 1,662 once invoked, about $0.0007 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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