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 kalyvask/winning-writing --skill style-tellsgit clone --depth 1 https://github.com/kalyvask/winning-writingWrote 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/kalyvask/winning-writing/style-tells)<a href="https://agentmods.dev/skills/kalyvask/winning-writing/style-tells"><img src="https://agentmods.dev/badge/skills/kalyvask/winning-writing/style-tells/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/kalyvask/winning-writing/style-tells"><img src="https://agentmods.dev/badge/skills/kalyvask/winning-writing/style-tells.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 | $0.00173 | $0.02927 |
| Opus 5 | $0.00086 | $0.01463 |
| Sonnet 5 | $0.00035 | $0.00585 |
| Haiku 4.5 | $0.00017 | $0.00293 |
Grade A, and why
style-tells 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 — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Style tells
Source: points/ai-writing-rules.md (em-dash rule), points/core-rules.md rule 5 (be shorter), points/banned-jargon.md, and Stephen King's On Writing (the adverb rule).
What this skill does
Three passes behind one skill. Each pass removes a different surface tell that flags writing as AI-generated, padded, or jargon-heavy:
| Target | What it removes | When to run alone |
|---|---|---|
| em-dashes | em-dashes (—), double-hyphens (--), the "not just X — it's Y" construction | When the only problem is AI-flavored punctuation |
| adverbs | empty intensifiers, -ly adverbs the verb already implies, sentence-starting adverbs | When the draft is bloated with qualifiers |
| jargon | banned consultant words, AI-tell phrases, wordy substitutions | When the draft sounds corporate or AI-generated |
Default --target all runs all three in order: jargon → adverbs → em-dashes. The order matters: jargon and adverbs often expose dashes that were holding bloated clauses together.
How to invoke
/style-tells "draft text"
/style-tells --target em-dashes "draft text"
/style-tells --target adverbs "draft text"
/style-tells --target jargon "draft text"
/style-tells --target all "draft text"
Without --target, default to all.
Target 1 — em-dashes
In 2026 the em-dash is the #1 AI tell. Models love them. Humans use them sparingly. A draft with twelve em-dashes per page is a confession that an AI wrote it.
Format limits
| Format | Em-dashes allowed |
|---|---|
| Cold email | Zero |
| Memo / status update | Zero |
| Slack message | Zero |
| LinkedIn post | One, max |
| Op-ed / essay | One per page (~250 words), max two |
| Substack post | One per major section break |
Over the limit → scrub.
Substitution table
| Pattern | Rewrite options |
|---|---|
X — Y (parenthetical aside) |
X (Y) or X, Y, or X: Y |
X — and Y (continuing thought) |
X. And Y. or X, and Y |
X — Y — Z (interrupted clause) |
X, Y, Z (commas) or X. Y. Z. (sentences) |
If — and only if — Z |
If, and only if, Z |
I built X — A, B, C — from scratch |
I built X from scratch: A, B, C. |
She said — wait, did she? |
She said. Wait, did she? |
It's not just X — it's Y (AI tic) |
Cut entirely. Rewrite without the construction. |
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 · 270 lines · 173 tokens per session scan A b5b610d0c246
style-tells is a skill published in the GitHub repository kalyvask/winning-writing (13 stars, last pushed 5d ago), licensed MIT. It adds 173 tokens to every session and 2,927 once invoked, about $0.0009 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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