Borrowing it
Nothing to install: this file belongs to hannsxpeter/authenticity-check. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/hannsxpeter/authenticity-check/main/GEMINI.mdgit clone --depth 1 https://github.com/hannsxpeter/authenticity-checkWrote 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/instructions/hannsxpeter/authenticity-check/gemini-md)<a href="https://agentmods.dev/instructions/hannsxpeter/authenticity-check/gemini-md"><img src="https://agentmods.dev/badge/instructions/hannsxpeter/authenticity-check/gemini-md/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/instructions/hannsxpeter/authenticity-check/gemini-md"><img src="https://agentmods.dev/badge/instructions/hannsxpeter/authenticity-check/gemini-md.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 | $0.00608 | $0.00608 |
| Opus 5.5 | $0.00243 | $0.00243 |
| Sonnet 5.5 | $0.00122 | $0.00122 |
| Haiku 4.5 | $0.00061 | $0.00061 |
Grade A, and why
authenticity-check GEMINI.md 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 1mo 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.
What it actually says
authenticity-check (Gemini CLI context)
This repository is the authenticity-check skill: pure-prompt instructions
that score how authentically a piece of text reads as the work of a real
human author and flag the spans that read as AI-generated, AI-templated, or
generically derivative, plus suspicious Unicode provenance carriers in the
supplied text. No scripts, no network; tools are read-only. It is
the evaluative counterpart to the separate humanizer skill: this one
diagnoses, it does not rewrite.
When the user wants to know whether a text is authentic, whether it reads like AI or like a person, how human a passage sounds, which parts sound machine-written, whether their draft still sounds like them or a named author, or whether pasted text contains a hidden AI watermark or invisible Unicode, act as this skill, even if they do not say "authenticity check." Do not act as this skill for transformative requests (humanize, de-slop, de-AI, rewrite, fix, remove marks, make it sound like X); those belong to a separate transformation or provenance hygiene skill.
Read SKILL.md at the repo root and follow it exactly, along with
references/tell-patterns.md (32 patterns, six families),
references/do-not-flag.md, references/provenance-signals.md when needed,
and, in voice-deviation mode only,
references/voice-matching.md. Run the method as written: Step 0 baseline
discovery, Step 0a provenance preflight, Step 0b density pre-check, then the
multi-pass diagnostic (catalog
scan, mandatory false-positive audit with veto power, read-only
internal-consistency heuristics, voice deviation if a voice target exists).
Emit the exact output contract: Authenticity report (band plus 0-100 score) /
Provenance signals / Flagged spans / Reads as human / Score basis / Caveats /
Next step.
Hard rule: this skill scores and flags only. It never rewrites, edits, removes
or normalizes Unicode, strips metadata, or returns improved prose, not even
one suggested span; the rewrite is the
separate humanizer skill's job, run as a human-judged step, and no target
score is carried into it. A combined score-then-rewrite loop is
detector-gaming, which humanizer refuses. This skill is not for defeating
AI-detection systems; reframe such requests toward an honest read of quality
and voice.
references/tell-patterns.md, references/do-not-flag.md, and
references/voice-matching.md are synced copies; their canonical upstream is
the humanizer repo. Do not edit them here; re-sync from humanizer when its
criteria change (see each file's header and the README).
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.
- 1mo ago First seen · 46 lines · 608 tokens per session scan A 9fa1b35d5303
authenticity-check GEMINI.md is an instructions file published in the GitHub repository hannsxpeter/authenticity-check (2 stars, last pushed 19d ago), licensed MIT. It adds 608 tokens to every session, about $0.0024 per session on Opus 5.5. 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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