「nda」の検索結果

Author, lint, and publish skill packages that satisfy the library authoring standard. Use when creating a new skill, reviewing a skill PR, or fixing one that never activates.

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Audit and repair an internal knowledge base — staleness, ownership gaps, orphans, duplication, and findability. Use when the wiki is untrusted, docs are out of date, nobody owns pages, or search returns the wrong answer.

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Deploy to AWS Elastic Beanstalk, in either Beanstalk Standard mode (EC2) or Beanstalk Cluster mode (managed EKS). Triggers on: elastic beanstalk, EB, beanstalk standard, beanstalk cluster, managed EC2 platform, web app with managed patching, worker on EC2, Heroku alternative, don't want to manage servers or container orchestration, migrate from Heroku, managed operational lifecycle, containerised app without operating Kubernetes, several services sharing a managed cluster, managed EKS without kubectl. Covers web and worker applications on EC2, and containerised single- and multi-service applications on managed EKS.

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Build a content calendar: topics by platform and date, pillar and funnel tags. "plan next month's content"

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Benchmark LLM reference recommendation capabilities by verifying every cited paper against Crossref, PubMed, arXiv, and DBLP. Measures hallucination rate, per-field accuracy (title/author/year/DOI), discipline breakdown, and year constraint compliance. Supports tool-augmented (ReAct + web search) mode. Use when the user asks to evaluate, benchmark, or compare models on academic reference hallucination, literature recommendation quality, or citation accuracy.

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Benchmark LLM reference recommendation capabilities by verifying every cited paper against Crossref, PubMed, arXiv, and DBLP. Measures hallucination rate, per-field accuracy (title/author/year/DOI), discipline breakdown, and year constraint compliance. Supports tool-augmented (ReAct + web search) mode. Use when the user asks to evaluate, benchmark, or compare models on academic reference hallucination, literature recommendation quality, or citation accuracy.

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When the user wants multiple expert perspectives on a marketing question — a simulated board of advisors staffed by legendary marketers (Seth Godin, David Ogilvy, Eugene Schwartz, April Dunford, Rory Sutherland, Alex Hormozi, Byron Sharp, and more). Also use when the user mentions 'marketing council,' 'board of advisors,' 'advisory board,' 'what would Seth Godin say,' 'what would Ogilvy think,' 'channel Hormozi,' 'get multiple perspectives,' 'debate this,' 'have the council review,' 'marketing mentors,' or asks how a famous marketer would approach their problem. The council gives each advisor's take through their documented frameworks, surfaces where they disagree, and synthesizes a recommendation. For executing the winning direction, hand off to positioning, offers, copywriting, ads, or the relevant skill.

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Drafts a customized Customer Agreement starting from the Y Combinator standard form SaaS template. Tailors the agreement through structured intake questions covering fee structure, data handling, ML rights, implementation services, and more. Applies 18 always-on defaults that transform the raw YC form into a professional starting point (renamed to "Customer Agreement", data privacy section added, warranty restructured, consolidated SLA/support exhibit, etc.). Produces a clean .docx and a lawyer-facing memo explaining every change from the YC standard. Use when user says "draft a SaaS agreement", "YC SaaS", "startup SaaS contract", "customer agreement", "SaaS subscription agreement", or "I need a SaaS agreement starting from the YC form". Also trigger when the user is a startup founder discussing SaaS contracting, even if they don't mention YC specifically.

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Pick the right LLM for CONTRACT REVIEW — reviewing an existing agreement for risk, deviations from standard, missing protections, and internal contradictions, and proposing redlines. Vendor-neutral routing grounded in mid-2026 legal benchmarks. Contract review is a COMPOSITE skill (extraction + reasoning + redlining + conflict-detection), so this routes by the dominant sub-task. Asks up to 4 quick questions (cost, speed, accuracy/stakes, privacy/jurisdiction/ language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model to review this contract / NDA / MSA", "best AI to redline", "route this contract review", or is about to review an agreement without a fixed model.

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RFP creation, distribution, evaluation, and shortlisting for in-house legal teams selecting outside counsel. Draft a new legal services RFP from scratch, evaluate firm responses against weighted criteria, produce a shortlist recommendation with selection rationale for GC sign-off, or design the end-to-end RFP process from scratch. Trigger on: 'draft an RFP', 'run an RFP process', 'evaluate firm responses', 'score the RFP submissions', 'which firms should we shortlist', 'selection recommendation', 'how do we run a panel RFP', 'RFP for legal services', 'pitch process', 'firm selection process', 'compare the proposals', 'we're reviewing our panel', 'panel refresh RFP', 'we need to go to market', 'request for proposal', 'evaluate the pitches', 'which firm won the RFP', 'write a legal RFP', 'RFP evaluation criteria', 'design the RFP process', 'how do we weight the criteria'.

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Generates standalone interactive HTML "deal cards" that translate complex regulations into negotiation-ready reference tools, systematically distinguishing mandatory obligations from negotiable implementation choices. Use when the user needs an interactive regulatory guide for (1) contract negotiation support, (2) client education or internal training, (3) regulatory briefings for commercial stakeholders, or (4) structured comparison between required and flexible compliance paths. Primary focus on EU digital regulation (Data Act, AI Act, CRA, DORA, NIS2, GDPR) but the structural pattern transfers to any regulation where separating hard obligations from implementation choice is the point. Supports bilingual output where the jurisdiction calls for it.

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Guide to review incoming one-way (unilateral) commercial NDAs in a jurisdiction-agnostic way, from either a Recipient or Discloser perspective (user-selected), producing a clause-by-clause issue log with preferred redlines, fallbacks, rationales, owners, and deadlines.

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Read, search, and download emails and attachments from Microsoft Outlook via OAuth2. Use when the user asks to (1) check, read, or fetch emails or messages from Outlook, (2) search emails by keyword, sender, or subject, (3) download email attachments such as contracts, NDAs, or documents, (4) chain email content into other skills (e.g. "read the latest email from X and review the attached NDA"), or (5) any task involving Microsoft Outlook, Office 365, or Exchange email access.

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Audits the transition from legal AI output to reliance, recommendation, execution, or real-world commitment. Use it before an AI-generated analysis, memo, contract review, compliance finding, or workflow output is acted upon to check whether authority, evidence, mandate, uncertainty, procedure, and review conditions remain sufficient.

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Mandatory external verification workflow for ALL non-trivial factual claims before presenting them as true. This skill MUST be used whenever Claude is asked to research any topic, answer factual questions, provide current information, draft documents containing factual claims, give legal advice or cite legal authority, discuss current events or public figures, provide technical or scientific information, state statistics or data points, or answer ANY question where the answer could have changed over time. Also trigger when the user asks Claude to 'check', 'verify', 'confirm', 'research', 'look up', or 'find out' anything, or when the user needs information that requires freshness, precision, or source accuracy. This skill overrides any default tendency to answer from memory. If a task involves stating facts, citing sources, or providing current information — use this skill.

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Expertise complète en droit français des étrangers, de l'asile et de la nationalité — entrée et visas, séjour (CESEDA livre IV, AES, étranger malade, regroupement familial, métiers en tension), éloignement et contentieux (OQTF, IRTF, rétention, référés, TA/CAA/CE), asile (OFPRA, CNDA, Dublin, CMA/ADA), nationalité et droits sociaux des étrangers (AME, PUMa, RSA, AAH, ASPA). Interroge en priorité trois connecteurs MCP complémentaires — OpenLegi (textes, jurisprudence administrative), LibreJustice (recherche sémantique tous ordres) et Legal Data Hunter (rétention/JLD, graphe de citations, statut de validité) — puis les sources officielles (Légifrance, ANEF, OFPRA, CNDA) et la doctrine associative (GISTI, Cimade, ADDE, Comede, Anafé). Déclencher dès qu'une question porte sur un étranger en France, même sans vocabulaire juridique — « papier de la préfecture », « récépissé périmé », « la CAF refuse le RSA » — et pour toute consultation, recours, note ou vérification de références dans ces matières.

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Assess whether a Fundamental Rights Impact Assessment (FRIA) is required under Article 27 EU AI Act, and structure or draft that assessment for a specific high-risk AI deployment. Covers deployer scope gating (public bodies and private entities providing public services), affected group mapping, Charter rights analysis, proportionality, safeguards evaluation, residual risk, DPIA/FRIA cross-referencing under the amended Article 27(4), the unconditional notification duty under Article 27(3), and DACH-specific considerations. Use when asked about FRIA obligations, Article 27 scope, fundamental rights and AI, or deployer assessment duties.

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Expert guidance for FedRAMP certification and compliance under CR26 (FedRAMP Consolidated Rules for 2026). Use this skill whenever a user asks about FedRAMP authorization, ATO (Authority to Operate), cloud security for federal government, NIST SP 800-53 controls, CSP compliance, or any of the core FedRAMP document types: SSP, SAP, SAR, POA&M, CIS/CRM workbooks. Also trigger for questions about FedRAMP Certification Classes (A, B, C, D — new baseline labels: A = pilot/transitional, B = LI-SaaS/Low, C = Moderate, D = High, per NTC-0004), FedRAMP 20x (now the primary authorization pathway), OSCAL mandate (September 2026), 3PAO assessments, continuous monitoring (ConMon), gap assessments, system boundary definition, or architecture reviews for federal cloud. FedRAMP Ready retires July 28, 2026. When in doubt, use this skill — it covers the full FedRAMP lifecycle from readiness through continuous monitoring.

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Index analytiques sourcés du corpus réglementaire et doctrinal sur la gouvernance des émetteurs cotés français (rapports AMF et HCGE 2020-2025, guide d'application HCGE, rapport sénatorial Rietmann/Gay, Code AFEP-MEDEF, sources légales et européennes). À utiliser pour : (1) retrouver une position, une statistique ou une citation exacte avec sa source et sa page ; (2) analyser l'évolution longitudinale des positions AMF/HCGE/ESMA sur un thème ; (3) appliquer la grille d'analyse en 13 blocs (A-M) à un émetteur. Déclencher pour toute question sur la gouvernance d'une société cotée française : conseil d'administration, indépendance des administrateurs, comités, rémunération des dirigeants, say on pay, say on climate, assemblée générale, droits des actionnaires, plans de succession, mixité, RSE/CSRD, comply-or-explain, name and shame AMF, soft law AFEP-MEDEF, recommandations AMF, positions HCGE.

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Review legal contracts, NDAs, employment agreements, SaaS terms, and M&A documents. Identifies unfavorable terms, suggests redlines, and compares to market standards. Use for contract analysis, due diligence, or negotiation prep.

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Contract intelligence and contract operations workflow skill for Claude and Codex. Guides the full contract lifecycle review process from intake and playbook normalization through clause review, deviation scoring, negotiation planning, approval routing, QA, and action recommendations. Reviews legal, business, operational, compliance, privacy, security, technology, and AI-related risks across contracts and legal documents. Supports NDAs, SaaS agreements, DPAs, procurement contracts, commercial agreements, contract comparisons, redlines, approval packages, clause research, and drafting. Warning-Comprehensive reviews can consume significant Claude/OpenAI tokens, especially for large agreements, playbooks, exhibits, schedules, and multi-document reviews.

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Map which elements of an assignment benefit from AI assistance vs. which AI use undermines. Use when redesigning tasks for AI-age classrooms or setting defensible AI use policies for specific assignments.

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Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

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Expert patterns for Godot 3D PBR materials using StandardMaterial3D including albedo, metallic/roughness workflows, normal maps, ORM texture packing, transparency modes, and shader conversion. Use when creating realistic 3D surfaces, PBR workflows, or material optimization. Trigger keywords: StandardMaterial3D, BaseMaterial3D, albedo_texture, metallic, metallic_texture, roughness, roughness_texture, normal_texture, normal_enabled, orm_texture, transparency, alpha_scissor, alpha_hash, cull_mode, ShaderMaterial, shader parameters.

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