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概要と使いどころ

>Ce skill génère des sujets d'entraînement pour les deux épreuves écrites de consultation du CRFPA : l'épreuve de droit des obligations (tronc commun) et l'épreuve de spécialité (civil, affaires, social, pénal, administratif, international et européen, fiscal). Chaque sujet est accompagné d'une grille de notation détaillée sur 20 points. Vous ciblez un thème précis, ou vous laissez le skill procéder à un tirage au sort couvrant l'ensemble du programme. Connexion aux MCP OpenLegi et GoodLegal requise : toutes les références d'articles et d'arrêts sont vérifiées sur les sources officielles, sans citation inventée

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

Adjudicates whether a hit generated by sanctions, PEP, or adverse-media screening is a true positive, false positive, or requires human escalation. Use whenever a user presents a screening alert, a name match against a watchlist (OFAC SDN, EU consolidated list, UK OFSI, UN list, PEP list, adverse media hit, etc.), or asks to clear a screening hit / reduce false positives / determine whether a flagged name is actually the listed party. Use even when the user describes the task casually — "is this person actually on the sanctions list", "did we get a real match", "clear this alert", "I have a hit on X" — these are all screening-adjudication tasks. Produces a deterministic determination with full audit trail (structured JSON + human-readable narrative). Designed for use by compliance analysts and screening systems.

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

Critically assess and improve a legal scholarly thesis, article idea, student note, seminar-paper claim, or research agenda using Eugene Volokh's novelty, nonobviousness, utility, and soundness framework, connector-aware research, claim-specific tests, and a sustainable adversarial pass. Produces a self-contained green-, yellow-, or red-light report. Use when a law professor or law student asks whether a claim is viable, novel, publishable, preempted, useful, worth pursuing, or better than competing topics; or wants a thesis stress-tested, narrowed, repaired, or compared. No connector is required: use connected legal and scholarly research when available, public sources otherwise, and disclose any no-research fallback.

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

Panel structure design, firm selection criteria, right-sourcing analysis, and coverage gap assessment for in-house legal teams. Build panel frameworks from scratch or formalise existing informal arrangements. Define weighted selection criteria for firm evaluation. Run right-sourcing analysis (ABC tiering) to identify work sent to expensive providers that doesn't require that level of resource. Assess existing panels for practice area, geographic, and capability gaps. Trigger on: 'design our panel', 'how many firms do we need', 'panel structure', 'firm selection criteria', 'which firms should we use', 'right-sourcing', 'are we sending work to the right firms', 'panel gaps', 'too many firms', 'consolidate our panel', 'we need a firm for', 'preferred provider', 'panel tiers', 'do we need BigLaw for this', 'convergence', 'D&I panel targets', 'how do we choose firms'.

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

La compétence Normalisation juridique FR nettoie un document Word rédigé en français juridique. Elle distingue deux régimes : les corrections déterministes (apostrophes courbes, guillemets français, espaces insécables, insécables des références — art. 1240, n° 21-12.345, 50 % —, ordinaux 1ère → 1re, ligatures œ, la loi dispose et non stipule, anglicismes-calques), appliquées directement ; et les réécritures de jugement (virgule avant « et », ternaires creux, formules emphatiques, harmonisations), posées en révisions Word soumises à votre acceptation. Chaque changement est consigné et restitué en tableau récapitulatif : on revient en arrière mot à mot — « défais 3, 7-10 ». La normalisation des citations reste purement formelle. Fonctionne en Cowork ou sur fichier Word.

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

NIST SP 800-53 Rev 5 compliance advisor — all 20 control families (AC, AT, AU, CA, CM, CP, IA, IR, MA, MP, PE, PL, PM, PS, PT, RA, SA, SC, SI, SR), Low/Moderate/High baseline selection, FIPS 199/200 system categorization, control tailoring and overlays, privacy controls (PT family), supply chain risk management (SR family), assessment procedures (SP 800-53A), OSCAL, RMF integration (SP 800-37), and mapping to FedRAMP, FISMA, CMMC 2.0, and ISO 27001. Use for any federal system security controls, FISMA compliance, RMF step guidance, control narrative writing, or baseline tailoring question.

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

Create original, competition-ready commercial mediation problems and confidential packets with iterative validation. Use when a user provides a topic, industry, dispute sketch, or existing general-information packet and wants a public packet plus confidential packets for both sides—or one named side. Build a narrow but workable settlement corridor; verify factual and numerical consistency, information asymmetry, balance, originality, and commercial feasibility; and revise until deterministic and semantic exit criteria pass. Do not use merely to summarize an existing packet or to advise parties in a real dispute. Requires local file access; Python 3 is recommended for bundled deterministic checks, with disclosed manual fallbacks when unavailable.

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

Orientação LGPD para operações de tratamento no Brasil. Cobre bases legais (Art. 7º e Art. 11), RIPD, incidentes (Arts. 48-49), direitos dos titulares (Art. 18) e transferências internacionais. Triggers: LGPD, RIPD, ANPD, proteção de dados, dados pessoais, consentimento, encarregado, DPO Brasil, incidente de dados, legítimo interesse.

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

Research, drafting, and analysis involving the International Criminal Court (Rome Statute system). Enforces a verification-first methodology — every case-law, decision, filing, warrant, and statement citation is verified against an authoritative primary source (icc-cpi.int, legal-tools.org) in the current conversation before it appears in an output. Foundational texts (Rome Statute, Elements of Crimes, RPE, Regulations of the Court) may be cited from project knowledge when present. Use whenever the user is working with ICC case law, OTP statements, ASP documents, or ICC procedure.

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

Méthodologie « verification-first » pour les Chambres Africaines Extraordinaires (procès Hissène Habré, Dakar). Toute citation est vérifiée (forumchambresafricaines.org, legal-tools.org). Couvre le jugement du 30 mai 2016, l'arrêt d'appel du 27 avril 2017 (réparations de 82,290 milliards FCFA pour 7 396 victimes), et la compétence universelle. Aide à la recherche, pas un conseil juridique. Fait partie de la bibliothèque open source « Skills for International Justice » — méthodologie : github.com/jeannesulzer/international-criminal-tribunals-skills

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

eardraft

無料

Transforms reading-oriented prose into listening-optimized text for flat, neutral vocal delivery — TTS, podcasts, audiobooks, CLE audio. Carries a legal layer: case citations, section symbols, subsection lettering, Latin terms and footnotes are unspeakable as written, so a brief, opinion, statute, contract or memo needs them expanded, restructured or stripped before it can be listened to — and quoted authority is never rewritten. Use when converting written content for audio, preparing oral argument by ear, producing CLE or client-facing audio, or making a document listenable on a commute. Triggers on "make this listenable," "convert for audio," "optimize for reading aloud," "prepare for TTS," "make an audio version," "podcast script," "read this aloud." Supports English, French, Spanish, Italian, German and Portuguese; outputs plain text, ElevenLabs audio tags, or SSML for Amazon Polly, Google or Azure.

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

Review, draft, or redline a Data Processing Agreement (DPA / Auftragsverarbeitungsvertrag / AVV) under Art. 28 GDPR, or prepare a Joint Controller Arrangement under Art. 26 GDPR. Supports bilingual output (DE/EN), both controller- and processor-side perspectives, and two review depths — quick (Art. 28(3)(a)–(h) coverage) and negotiation-grade (clause-by-clause risk scoring).

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

When your bar comes asking "show me how you billed AI-assisted work" — and ABA 512, Florida 24-1, California, New York, and DC all have opinions out — you need an artifact that survives review. billable-time produces it. From your Claude Code session logs, it drafts reviewable time entries plus a printable HTML audit packet with: SHA-256 chain of evidence (source files + matter.yml + active disclosure pack + verifiable artifact self-hash), attorney identity and signature block, a bar-opinion disclosure pack with starter language for five jurisdictions, and content-aware deterministic narratives derived from filename and tool shape — never from prompt text by default. The tool refuses to bill on its own. --strict mode refuses to ship the artifact if any audit invariant fails (broad routes, missing attorney, missing/unverified disclosure). Comes as a Node CLI and a self-contained browser version (no backend; JSONL never leaves the page). 15 invariant tests verify the contract. AGPL-3.0.

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

Matter budgeting and ongoing WIP/variance monitoring. Build phase-based fee estimates at matter setup, run bottom-up budgets by jurisdiction or workstream, calculate contingency, and structure AFA arrangements (fixed fee, capped fee, phased fixed fees). Ongoing monitoring: WIP tracking against budget, proportionality assessment (spend vs progress), variance commentary with root cause analysis, forecast-to-complete, realisation monitoring, write-off analysis. Trigger on: 'build a budget', 'fee estimate', 'what will this cost', 'WIP review', 'budget vs actual', 'how are we tracking against budget', 'we're over budget', 'realisation is poor', 'what's our ETC', 'budget for the German workstream', 'model the financial impact of this scope change', 'draft a fee adjustment', 'write-off analysis', 'how much contingency', 'AFA structure', 'fixed fee estimate', 'budget update', 'forecast to complete'.

日本語の概要は準備中です。原文の説明を表示しています。

lawve-ai/awesome-legal-skills8672026年10月3日 更新

Synthesise completed KUD charts into a developmental progression matrix and per-competency narrative sections. Use when you need a programme-level view of how knowledge, understanding, and performance develop across bands.

日本語の概要は準備中です。原文の説明を表示しています。

GarethManning/education-agent-skills8652026年8月29日 更新

Tier vocabulary from a text or topic into everyday, academic, and technical categories with teaching priorities. Use when pre-teaching vocabulary or identifying language barriers in a text.

日本語の概要は準備中です。原文の説明を表示しています。

GarethManning/education-agent-skills8652026年8月29日 更新

Analyse the language demands of a classroom task to identify barriers for EAL and multilingual learners. Use when adapting tasks, planning support, or assessing linguistic accessibility.

日本語の概要は準備中です。原文の説明を表示しています。

GarethManning/education-agent-skills8652026年8月29日 更新

Map curriculum connections across multiple subjects for a real-world problem or authentic context. Use when planning cross-curricular projects or connecting content to real issues.

日本語の概要は準備中です。原文の説明を表示しています。

GarethManning/education-agent-skills8652026年8月29日 更新

Measure and shrink the always-loaded context of a Claude Code harness (CLAUDE.md + rules without paths frontmatter) back under budget — migrate narrative to reference files, convert rules to path-scoped or skill-triggered loading, and verify zero governance loss with deterministic preservation checks. Use on "harness diet", "context diet", "rules diet", "CLAUDE.md too long", "always-load budget", "trim my rules", "context bloat", "하네스 다이어트", "룰 다이어트", "컨텍스트 다이어트", "always-load 줄여줘". Not for one-off prose editing or project docs cleanup.

日本語の概要は準備中です。原文の説明を表示しています。

sangrokjung/claude-forge8572026年9月3日 更新

Expert Godot shader patterns for batch-safe hitflash, alpha-scissor foliage/dissolve, screenspace postFX, depth reconstruction, triplanar, and instance uniforms — not first-shader tutorials. Trigger on draw-call batching breaks, discard vs depth-prepass, foliage shadows, post-process quads, or world-position FX. Keywords: instance uniform, ALPHA_SCISSOR, hint_screen_texture, hint_depth_texture, global uniform, sampler2DArray, canvas_item, spatial, post-processing.

日本語の概要は準備中です。原文の説明を表示しています。

thedivergentai/Game-Dev-Agentic-Skills8562026年10月14日 更新

Expert blueprint for sandbox games (Minecraft, Terraria, Garry's Mod) with physics-based interactions, cellular automata, emergent gameplay, and creative tools. Use when building open-world creation games with voxels, element systems, player-created structures, or procedural worlds. Keywords voxel, sandbox, cellular automata, MultiMesh, chunk management, emergent behavior, creative mode.

日本語の概要は準備中です。原文の説明を表示しています。

thedivergentai/Game-Dev-Agentic-Skills8562026年10月14日 更新

Expert patterns for branching dialogue systems including dialogue graphs (Resource-based), character portraits, player choices, conditional dialogue (flags/quests), typewriter effects, localization support, and voice acting integration. Use for narrative games, RPGs, or visual novels. Trigger keywords: DialogueLine, DialogueChoice, DialogueGraph, dialogue_manager, typewriter_effect, branching_dialogue, dialogue_flags, localization, voice_acting.

日本語の概要は準備中です。原文の説明を表示しています。

thedivergentai/Game-Dev-Agentic-Skills8562026年10月14日 更新

Expert Godot shader patterns for batch-safe hitflash, alpha-scissor foliage/dissolve, screenspace postFX, depth reconstruction, triplanar, and instance uniforms — not first-shader tutorials. Trigger on draw-call batching breaks, discard vs depth-prepass, foliage shadows, post-process quads, or world-position FX. Keywords: instance uniform, ALPHA_SCISSOR, hint_screen_texture, hint_depth_texture, global uniform, sampler2DArray, canvas_item, spatial, post-processing.

日本語の概要は準備中です。原文の説明を表示しています。

thedivergentai/Game-Design-Agentic-Skills8502026年10月13日 更新

Expert patterns for branching dialogue systems including dialogue graphs (Resource-based), character portraits, player choices, conditional dialogue (flags/quests), typewriter effects, localization support, and voice acting integration. Use for narrative games, RPGs, or visual novels. Trigger keywords: DialogueLine, DialogueChoice, DialogueGraph, dialogue_manager, typewriter_effect, branching_dialogue, dialogue_flags, localization, voice_acting.

日本語の概要は準備中です。原文の説明を表示しています。

thedivergentai/Game-Design-Agentic-Skills8502026年10月13日 更新