Rédaction de requêtes devant le Conseil de prud'hommes pour contester un licenciement pour faute grave. Utiliser ce skill quand l'utilisateur demande de rédiger une requête CPH, contester un licenciement pour faute grave, préparer une saisine du CPH pour un litige lié à un licenciement, ou créer un document de contestation de licenciement en droit du travail français.
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Ce skill guide la rédaction de requêtes devant le Conseil de prud'hommes (juridiction du travail français) pour un salarié contestant son licenciement pour faute grave et demandant la requalification en licenciement sans cause réelle et sérieuse.
Avant de rédiger la requête, impérativement collecter les informations suivantes auprès de l'utilisateur :
Expliquer au salarié les différentes indemnités possibles et l'aider à les calculer :
Collecter toutes les informations listées ci-dessus de manière interactive avec l'utilisateur. Voir conseils-variations.md pour un exemple de dialogue.
Calculer les montants des différentes indemnités. Consulter calculs-indemnites.md pour les formules et barèmes.
Rédiger la requête en suivant la structure en 9 parties. Consulter structure-requete.md pour le template complet.
Vérifier la cohérence du document. Voir la section "Finalisation" dans conseils-variations.md.
Créer le document final en format .docx et le présenter à l'utilisateur.
Structure de la requête : Voir structure-requete.md pour le template complet des 9 parties (en-tête, identification des parties, avertissements légaux, rappel des faits, exposé des motifs, demandes, par ces motifs, signature)
Calculs des indemnités : Voir calculs-indemnites.md pour les formules de calcul du salaire de référence, de l'ancienneté, de l'indemnité légale de licenciement, du préavis, et le barème des indemnités pour licenciement sans cause réelle et sérieuse
Conseils et variations : Voir conseils-variations.md pour la jurisprudence clé, les conseils de rédaction, les points de vigilance, les exemples de dialogue, les variations selon les situations, et la checklist de finalisation
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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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