Rédaction d'assignations en référé devant le tribunal de commerce ou des activités économiques pour le recouvrement de créances commerciales. Utiliser ce skill quand l'utilisateur demande de rédiger, préparer ou créer une assignation en référé pour obtenir le paiement d'une créance impayée (factures, prestations de services, ventes de marchandises, etc.) lorsque le débiteur n'a pas honoré ses obligations de paiement et qu'il n'existe pas de contestation sérieuse.
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Ce skill guide la rédaction d'assignations en référé devant le président du tribunal de commerce ou des activités économiques lorsqu'un créancier demande la condamnation de son débiteur au paiement d'une créance certaine, liquide et exigible, en l'absence de contestation sérieuse.
Fondement : Article 873 alinéa 2 du Code de procédure civile (compétence du juge des référés en l'absence de contestation sérieuse).
Principe clé : Le juge des référés peut accorder une provision au créancier ou ordonner l'exécution d'une obligation dès lors que l'existence de l'obligation n'est pas sérieusement contestable.
Collecter toutes les informations nécessaires auprès de l'utilisateur. Consulter workflow-collecte.md pour les 6 phases de questions à poser :
Rédiger l'assignation en suivant la structure en 5 parties. Consulter structure-assignation.md pour le template complet :
Adapter la rédaction selon le type de créance. Consulter variantes-cas-particuliers.md pour :
Vérifier la cohérence du document. Consulter conseils-strategie.md pour :
Créer le document final en format .docx et le présenter à l'utilisateur.
Structure de l'assignation : Voir structure-assignation.md pour le template complet des 5 parties (en-tête, avertissements, corps avec faits et discussion, dispositif, bordereau de pièces)
Workflow de collecte : Voir workflow-collecte.md pour les 18 questions à poser à l'utilisateur réparties en 6 phases
Variantes et cas particuliers : Voir variantes-cas-particuliers.md pour les adaptations selon le type de créance (services, marchandises, travaux), les montants, et les situations particulières (contestation partielle, compensation, clause résolutoire)
Conseils et stratégie : Voir conseils-strategie.md pour les points clés de rédaction, la checklist finale complète, les montants usuels, et la stratégie procédurale (provision vs condamnation définitive, référé vs injonction de payer)
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Public-safe preliminary screen for challenges to the impartiality of an AI evaluator, LLM-as-a-judge, decision-support agent, or adjudicative system based on prior outputs, suspected bias, unstable reasoning, or self-reinforcing memory. Use when asked whether an AI should be recused, disqualified, replaced, audited, or escalated. Does not decide real cases or claim that human judicial-recusal doctrine automatically applies.
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Creates an Agent Authority Charter for enterprise or regulated AI agents before deployment. Use this Skill when a user needs to define what an AI agent is allowed to do, who delegated authority to it, what actions are permitted or prohibited, when human approval is required, what evidence must be preserved, and how the agent can be suspended, revoked, or escalated.
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EU AI Act Knowledge Engine — authoritative regulatory Q&A grounded in 70 official EU source documents (including the 2026 Commission draft guidelines on Art. 6 high-risk classification — general principles, Annex I, Annex III). Answers any question about the AI Act with article-level citations from the full regulation text, Commission guidelines, EDPB/EDPS opinions, codes of practice, harmonised standards, FRIA guides, incident templates, and sector-specific guidance. This skill should be used when the user asks about the "EU AI Act", "AI Act regulation", "Regulation 2024/1689", "KI-Verordnung", asks to "explain an AI Act article", "what does Article X say", "AI Act requirements", "AI Act penalties", "AI Act timeline", "GPAI obligations", "high-risk AI", "prohibited AI practices", "AI Act and GDPR", "fundamental rights impact assessment", "AI Act standards", "AI Act national implementation", "AI literacy", "serious incident reporting", "Digital Omnibus", "AI regulatory sandbox", or any question about EU artificial intelligence regulation. Also triggers on German terms: "KI-Gesetz", "KI-Verordnung", "Hochrisiko-KI", "KI-Kompetenz", "Grundrechte-Folgenabschaetzung", "GPAI-Verhaltenskodex". For assessment workflows that produce a classification decision rather than a knowledge answer, offer to run a structured risk-tier classification in-session.
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This skill builds a structured audit trail of an AI-assisted task: what the tool was asked to do, what materials it was given, what it produced, how the output was verified, and what was ultimately relied upon. It documents the workflow for supervision and later review without ruling on privilege or disclosure, so the record stays accurate rather than self-serving.
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Use this skill when the user wants an AI governance, legal-risk, privacy, compliance, procurement, or vendor-risk review of an internal AI use case, an AI product feature, an LLM workflow, or a third-party AI vendor. The skill asks intake and clarifying questions first when facts or evidence are missing, identifies required documentation and missing evidence, maps the use case to AI governance frameworks and applicable legal domains, and produces a preliminary or final governance review with scorecards, findings, owners, remediation actions, and follow-up questions.
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Turn an interpretive-ambiguity audit of a legal text — contract, statute, regulation, or judicial opinion — into a polished deliverable. Produces a multi-page website (default), a single-page interactive site, a Microsoft Word document, a PowerPoint deck, or a LaTeX/PDF. Use whenever a user has a stress-test result, ambiguity audit, or "where will this be litigated" scenarios and wants to publish, present, or share them. Triggers on "publish the audit," "make a report from this," "turn this into a website / deck / brief / Word doc," "make a Netlify site," "build slides of these ambiguities," "render the scenarios," "package this stress test," "produce a LaTeX version," and similar. Pairs with the ambiguity-stress-test skill (the underlying analysis) but works on any structured or semi-structured ambiguity analysis. Visual design is opinionated but the user can override colors, fonts, and brand label. Most formats need Python and a writable filesystem; single-file HTML works where the host has neither.
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