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 agentmods add skills/ne11nn/cantos-plugin/write-like-menpx skills add ne11nn/cantos-plugin --skill write-like-megit clone --depth 1 https://github.com/ne11nn/cantos-pluginWrote 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/ne11nn/cantos-plugin/write-like-me)<a href="https://agentmods.dev/skills/ne11nn/cantos-plugin/write-like-me"><img src="https://agentmods.dev/badge/skills/ne11nn/cantos-plugin/write-like-me.svg" alt="Measured on agentmods" 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 | $0.00083 | $0.00779 |
| Opus 5 | $0.00042 | $0.00390 |
| Sonnet 5 | $0.00017 | $0.00156 |
| Haiku 4.5 | $0.00008 | $0.00078 |
Grade A, and why
write-like-me 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 5d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: write-like-me
Invocation: /write-like-me, or triggers like "write this in my voice", "sound like me", "humanize this", "make this less AI", "draft as me", "in my words".
Produces text that reads like the USER wrote it: it matches their learned style and avoids AI-writing tells. This is the generative end of the writing pipeline — the opposite of ai-detect, which scans and scores. Use them together: write in voice here, verify the score with /ai-detect if the stakes are high.
Inputs
- The text to write (a brief or outline) or rewrite (an existing draft).
- Register:
professionalorcreative. If the user does not say, infer it (formal / work / academic → professional; personal / casual / narrative → creative) and state which you chose.
Step 1 — Load the voice
- Read
references/writing-voice/profile-{register}.md. - If it is still the placeholder (no profile has been generated), STOP. Tell the user folio needs to learn their voice first, and offer to run
workflows/folio/analyze_writing_voice.md. Do not fabricate a voice from nothing — a guessed voice is worse than asking. - Read
references/signs-of-ai-writing.md— the catalog of tells to avoid.
Step 2 — Write in voice
Draft (or rewrite) applying, in priority order:
- The profile's Do this patterns — reproduce the user's real habits: cadence, diction, stance, structure, openings and closings.
- The profile's Never do this list — do not introduce habits the user never uses.
- Against every tell in
references/signs-of-ai-writing.md— no significance inflation, no rule-of-three, no negative parallelisms ("not just X, but Y"), no em-dash overuse, no elegant variation, no copula avoidance, no mechanical transition uniformity, no perfect uniform polish, no filler phrases.
When rewriting, preserve the user's meaning and every fact. Change only the expression.
Step 3 — Self-audit before returning
Re-read the draft against three checklists and fix every miss:
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.
- 5d ago First seen · 68 lines · 83 tokens per session scan A 58f5f62539af
write-like-me is a skill published in the GitHub repository ne11nn/cantos-plugin (1 stars, last pushed today), licensed MIT. It adds 83 tokens to every session and 779 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.
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