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 PrendsTaPart/Plugin-Claude-MCP-BraindCode- --skill video-virale-platsgit clone --depth 1 https://github.com/PrendsTaPart/Plugin-Claude-MCP-BraindCode-Wrote 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/prendstapart/plugin-claude-mcp-braindcode-/video-virale-plats)<a href="https://agentmods.dev/skills/prendstapart/plugin-claude-mcp-braindcode-/video-virale-plats"><img src="https://agentmods.dev/badge/skills/prendstapart/plugin-claude-mcp-braindcode-/video-virale-plats/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/prendstapart/plugin-claude-mcp-braindcode-/video-virale-plats"><img src="https://agentmods.dev/badge/skills/prendstapart/plugin-claude-mcp-braindcode-/video-virale-plats.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 | $0.00088 | $0.00845 |
| Opus 5.5 | $0.00035 | $0.00338 |
| Sonnet 5.5 | $0.00018 | $0.00169 |
| Haiku 4.5 | $0.00009 | $0.00085 |
Grade A, and why
video-virale-plats 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.
How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vidéo virale de plats (photos réelles → Higgsfield → réseaux)
Le trio : FoodEatUp fournit la raison (plat star, plat du jour, surstock à écouler) et la marge, Higgsfield anime la vraie photo, RapidoCMS porte la charte et le brouillon de publication.
1. La matière première : de VRAIES photos
- Chercher les photos existantes du plat : assets de marque RapidoCMS
(
list_all_files→file_urlpubliques) ; sinon demander une photo à l'utilisateur (smartphone suffit) et l'héberger viaupload_file_tool(URL http(s) exigée par le hook rapidocms). - Règle d'honnêteté : pas de photo → pas de vidéo du plat. On peut faire une vidéo d'ambiance ou typographique, mais on ne génère jamais un faux plat photoréaliste présenté comme le vrai.
- Côté Higgsfield, importer la photo par URL (
media_import_url) avant de l'animer.
2. Fabrication (coût confirmé AVANT chaque étape payante)
models_explore(action recommend) avec l'objectif : « animer une photo de plat en vidéo courte appétissante » — ne pas deviner le modèle.generate_videoen image-to-video depuis la photo importée : mouvement court (vapeur, zoom lent, nappage), 6-10 s — c'est le format qui retient.reframepour décliner : 9:16 (Reels/TikTok/story), 1:1 (feed), 16:9 si besoin.upscale_videoseulement si la plateforme l'exige.virality_predictorsur le résultat : hook des 2 premières secondes, rétention, recommandations — régénérer UNE fois si le verdict est faible, puis montrer tel quel (pas de boucle infinie de crédits).- Habillage aux couleurs de la maison (texte, logo depuis la charte
get_brand) — le gate charte du skillfabrique-contenu-iriss'applique.
Chaque étape payante (génération, upscale, reframe) est annoncée avec son coût en crédits et attend l'accord — le garde-fou du plugin refuse toute génération vidéo sans coût confirmé.
3. Publication (jamais automatique)
- La vidéo finit en brouillon RapidoCMS (
upload_file_toolpuiscreate_draft_tool) avec sa copy et SA RAISON (« Parce que le burger signature dégage X % de marge et sort Y fois par semaine »). - La planification passe par le skill
calendrier-iris: validation humaine, garde-fou sur la planification. - La publication TikTok directe côté Higgsfield (
tiktok_publish) est également derrière confirmation — préférer le circuit brouillon CMS.
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 · 59 lines · 88 tokens per session scan A bb6610f79da6
video-virale-plats is a skill published in the GitHub repository PrendsTaPart/Plugin-Claude-MCP-BraindCode- (8 stars, last pushed 6d ago), licensed Apache-2.0. It adds 88 tokens to every session and 845 once invoked, about $0.0004 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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