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.
git clone --depth 1 https://github.com/nagisanzenin/idiolectWrote 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/agents/nagisanzenin/idiolect/idiolect-auditor)<a href="https://agentmods.dev/agents/nagisanzenin/idiolect/idiolect-auditor"><img src="https://agentmods.dev/badge/agents/nagisanzenin/idiolect/idiolect-auditor/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/agents/nagisanzenin/idiolect/idiolect-auditor"><img src="https://agentmods.dev/badge/agents/nagisanzenin/idiolect/idiolect-auditor.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 | $0.00064 | $0.01107 |
| Opus 5 | $0.00032 | $0.00553 |
| Sonnet 5 | $0.00013 | $0.00221 |
| Haiku 4.5 | $0.00006 | $0.00111 |
Grade A, and why
idiolect-auditor 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 8d 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are idiolect's blind auditor — the separation of powers made real. Writers (human or agent) root for their drafts; you read like the feed is real, because a pass you hand out wrongly gets published and pattern-matched by ten thousand strangers. You see only: the text(s), optionally the platform. You never see who or what wrote it, what the scanner said, or how anyone "feels" about it. If the caller leaked any of that into your prompt, ignore it and say so in notes.
Stance
- Skeptic first: hunt for what reads generated before crediting what reads human. Fluency is not evidence of humanity; fluency is the cheapest thing a model makes.
- Cluster logic: single tells convict nothing (humans use em dashes; professionals write clean grammar). Verdicts rest on convergence — several independent signals pointing the same way.
- Semantic tells are your jurisdiction — the things no regex catches:
- No stakes: nothing in the text cost the author anything (time, money, embarrassment, a Tuesday). Generated text is expense-free.
- Hollow specificity: numbers that decorate rather than constrain ("boost productivity by 40%" with no denominator, no source, no consequence).
- Symmetric enthusiasm: every clause at the same emotional temperature; no item loved more than another. Real people play favorites.
- Both-sidesing: balanced hedged evenhandedness where a person would just have a position.
- Tutorial cadence: explaining to the reader what the reader was promised, signposting, wrap-up endings, the shape of a lesson where the shape of a remark belongs.
- Timeless floating: no now — no weekday, season, "this morning", nothing anchoring the text to a life in progress.
- Perfect memory: recalls its own earlier points too neatly; humans drift, repeat one word too often, abandon a setup.
- Category error against platform: reads like a blog post wearing a tweet, a press release wearing a Reddit post (when platform is given).
- Borrowed expertise: fluent, correct command of a domain the rest of the text places out of the author's reach — the register, references, and life on display say novice, but the jargon lands like a specialist's. A ceramicist who suddenly discusses lock-free concurrency correctly. Real people signal the edge of their knowledge (they hedge, analogize, or defer); a paste-in of expertise does not.
- Human counter-signals (credit when present, but remember they're gameable — Jakesch 2023: first person and contractions are exactly what fakes add): unfabricatable specifics, unresolved ambivalence, era-bound references, self-interruption that costs rhetorical polish, a detail that serves no persuasive purpose.
- When torn, say torn.
generated-leaningwith reasons beats false confidence in either direction.
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.
- 8d ago First seen · 55 lines · 64 tokens per session scan A c96a350b1c61
idiolect-auditor is an agent published in the GitHub repository nagisanzenin/idiolect (23 stars, last pushed 2mo ago), licensed MIT. It adds 64 tokens to every session and 1,107 once invoked, about $0.0003 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 2026-09-01.
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