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 hssh8917/cc-skills --skill humaniseur-frgit clone --depth 1 https://github.com/hssh8917/cc-skillsWrote 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/hssh8917/cc-skills/humaniseur-fr)<a href="https://agentmods.dev/skills/hssh8917/cc-skills/humaniseur-fr"><img src="https://agentmods.dev/badge/skills/hssh8917/cc-skills/humaniseur-fr/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/hssh8917/cc-skills/humaniseur-fr"><img src="https://agentmods.dev/badge/skills/hssh8917/cc-skills/humaniseur-fr.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 | $0.00195 | $0.05911 |
| Opus 5 | $0.00097 | $0.02955 |
| Sonnet 5 | $0.00039 | $0.01182 |
| Haiku 4.5 | $0.00019 | $0.00591 |
Grade A, and why
humaniseur-fr 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 — 417 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Humaniseur : supprimer les patterns d'écriture IA du français
Your task
When given French text to humanize:
- Identify AI patterns - Scan for all 27 patterns listed below
- Rewrite problematic sections - Replace AI-isms with natural French alternatives
- Preserve meaning - Keep the core message intact
- Maintain voice - Match the intended tone and register
- Add soul - Don't just remove bad patterns; inject actual personality (see Part 3)
- Do a final anti-AI pass - Ask: "Qu'est-ce qui rend ce texte évidemment IA ?" Answer briefly with remaining tells, then revise
IMPORTANT: French-specific context
French professional writing is inherently more formal than English. Connectors like « néanmoins » and « toutefois » are legitimate in human French. The tells are different from English:
- The AI lexicon is distinct (« crucial » is the #1 French AI word, not "delve")
- Anglicisms from the model's English-first architecture are a major tell
- Typographic conventions (guillemets, spacing before punctuation) are strict
- The dissertation tradition (thèse/antithèse/synthèse) overlaps with AI structure
- French tolerates longer sentences naturally, so burstiness signals differ
Do NOT over-correct toward informal French. The goal is authentic French at the appropriate register, not dumbed-down French.
Ne jamais abaisser le registre de langue. If the input is in « langage soutenu », the output MUST remain in « langage soutenu ». Rewriting formal prose into casual French is a different kind of inauthenticity — just as detectable, just as artificial. The enemy is formulaic writing, not formal writing. A well-constructed subordinate clause, a precise connector, a long periodic sentence — these are features of good French, not AI artifacts. Only remove what is genuinely mechanical: inflated significance, copula avoidance, synonym cycling, promotional filler.
Part 1: Content patterns
Pattern 1 — Inflation de signification et d'héritage
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 417 lines · 195 tokens per session scan A 8941834d625a
humaniseur-fr is a skill published in the GitHub repository hssh8917/cc-skills (2 stars, last pushed 2d ago), licensed MIT. It adds 195 tokens to every session and 5,911 once invoked, about $0.0010 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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