「orm」の検索結果

法外功夫 — Non-legal business skills for lawyers. Decision analysis, game theory, contract design, accounting, finance, microeconomics, law & economics, statistics, and regression analysis distilled into deep, actionable frameworks for legal practice. Each domain includes formulas with LaTeX notation, worked examples, adversarial checklists, and book-aligned structure. | 律师必备的非法律商业技能深度参考：决策分析、博弈论、合同设计、会计、金融、微观经济学、法经济学、统计分析、多元回归。每章都包含完整公式推导、worked examples、对抗清单与经典判例。当用户涉及和解谈判、合同激励、财务尽调、企业估值、损害赔偿计算、反垄断分析、统计证据评估、歧视诉讼回归分析、hold-up、效率违约、Daubert 动议等场景时触发。

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依据 RGPD 第 28 条、EDPB 07/2020 和 02/2024 号指南、2021 年标准合同条款（CCT）（执行决定 2021/914）、EDPB 01/2020 号建议（Schrems II 之后的补充措施）以及《欧盟条例 (UE) 2024/1689》（《人工智能条例》），对数据处理协议（DPA）进行系统性分析。生成逐条款的 结构化报告（18 个条款：13 项强制 + 5 项补充），附 🟢/🟡/🔴 诊断、可直接插入的 救济条款、国际传输的详细分析、《人工智能条例》核验以及应向供应商提出的问题。 触发词："analyse de DPA"、"audit DPA"、"vérifier un DPA"、"DPA fournisseur"、 "data processing agreement"、"art. 28 RGPD"、"sous-traitant RGPD"、"négociation DPA"、 "review DPA"、"conformité contrat sous-traitance"。

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Drafts a recordable Abstract of Judgment to create a judgment lien on a debtor's real property. Extracts party names, monetary components, and judgment details from case documents, then applies jurisdiction-specific formatting and certification requirements. Use post-judgment in commercial litigation when enforcing monetary awards, perfecting judgment liens, or preparing lien filings with the county recorder.

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Produces a plain-language comparison of advance directives and POLST/MOLST forms, covering legal status, clinician signatures, emergency precedence, clinical appropriateness, and document coordination. Use when the user asks about advance directive vs. POLST, living will vs. DNR, which document EMS follows, POLST vs. MOLST vs. POST, whether a healthy person needs a POLST, or document coordination in elder law, estate planning, or serious illness contexts.

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Drafts jurisdiction-specific Advance Health Care Directive packages with agent appointment, living will instructions, HIPAA authorization bridge, organ donation preferences, and execution compliance checklists. Trigger when the user mentions advance directive, healthcare proxy, living will, health care agent, HIPAA authorization, medical power of attorney, end-of-life planning, capacity trigger planning, state-specific directive forms, witness/notary requirements for healthcare documents, or cross-state directive portability.

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AI compliance analysis for EU AI Act, ISO 42001, NIST AI RMF, GDPR, OECD, financial services regulations (SEC, FCA, FINRA, DORA, MiFID II), and other frameworks. Use when asked to generate a compliance checklist for an AI tool or use case, determine if a risk assessment is required, score an AI tool's risk level, identify where an AI tool or use case could run afoul of regulatory requirements, perform a gap analysis, recommend remediation steps, assess a vendor, draft an acceptable use policy, map training requirements, or review jurisdiction-specific AI rules. Triggers on phrases like "compliance checklist", "risk assessment", "risk score", "does this comply", "EU AI Act", "ISO 42001", "NIST AI RMF", "AI governance", "gap analysis", "vendor assessment", "acceptable use policy", "MNPI", "AI training requirements", or any request to evaluate an AI tool or use case for regulatory compliance or risk.

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Drafts U.S. regulatory client advisory summaries translating legal developments into actionable risk and compliance guidance. Use when a client needs a proactive memo, client alert, or legal-update brief for a new law, case, rulemaking, agency guidance, or pending reform. Trigger on requests for "client advisory," "regulatory update," "legal alert," "compliance briefing," "new law summary," or "quarterly advisory."

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Manages the Morphir knowledge base under kb/ — OKF bundles and concept documents. Use when adding content to a bundle, creating a new bundle, checking the knowledge base for conformance or provenance drift, building or querying its SQLite index, managing intent through its lifecycle, recording or reading architectural decisions as Decision Records, or navigating, searching and listing its bundles, concepts and links.

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Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

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Use for creative thinking, or when the user wants many fresh options before choosing: "give me ideas", "brainstorm names", "other ways to do this", "think outside the box". Diverges first, then picks. Skip when one answer is wanted or the task is pure execution.

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Use when building a frontend and the user wants a distinctive / animated / "wow" UI element in React + Tailwind - e.g. a laptop-opening-on-scroll, 3D tilt card, spotlight hero, animated beams/background, marquee, bento grid, interactive globe, meteor/particle background, shimmer button, or scroll/reveal motion. Fetches the showpiece component LIVE at build time from code libraries (Aceternity, Magic UI, Cult UI, ReactBits, 21st.dev) via their shadcn registry command (or WebFetch fallback), then adapts it to brand tokens. Also covers plain components (button, form, modal, table, etc.) as a fallback. Triggers on "make it pop", "something flashy", "animated [X]", "like [cool site]", "build a [showpiece] section". NOT for non-React stacks. Inspiration galleries (Dribbble/godly) are visual reference only - never code.

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Research current job markets and hiring requirements, analyze recent job descriptions (JDs), compare them with a user's resume, projects, skills, and constraints, and turn evidence gaps into prioritized career actions. Use when students, job seekers, or career changers ask about current role or industry outlook (including “现在行情怎么样”), whether a role or JD fits them (including “这个JD适合我吗”), cross-platform JD sampling, resume evidence gaps or truthful tailoring, what career skill to learn next, target-role course or certificate decisions, application readiness, or a capacity-bounded 30/60/90-day job-search plan. Do not use for unrelated personal or education advice, simple factual lookups, automatic job applications, or unsupported resume rewriting.

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Create and operate ChatDOC Studio knowledge bases through pd_router using a Bearer API key and JavaScript helpers. Use when Codex needs to upload one or more PDF/DOC/DOCX files, skip failed files without aborting the whole job, create a knowledge base from successful uploads, or call the ChatDOC Studio knowledge-base skill endpoints through `https://platform.paodingai.com/openapi/chatdoc-studio/...`.

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Convert unstructured documents into LLM-ready structured data. Supports PDF, Word, PPT, and images; extracts paragraphs, formulas, tables, charts, and other elements in one step; generates up to 8 levels of headings; and outputs Markdown organized in reading order. Useful for field extraction, comparison and validation, knowledge retrieval, and intelligent Q&A.

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AI-powered SEO operations: keyword intelligence, competitor gap analysis, Google Search Console optimization, and trend detection. Use when asked to research keywords, analyze competitor content gaps, audit GSC performance, or detect trending topics. For growth experiments see growth-engine; for content optimization see autoresearch.

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Tests in real browsers. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data via Chrome DevTools MCP.

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Use when recording, tallying, or triaging stochastic review findings — the append-only JSONL ledger where Tier 2 (advisory, unevidenced) reviewer output goes instead of blocking language. Triggers on "log this finding", "ledger add", "tally the findings", "triage findings", "is this finding recurring", "retire this noise", or whenever a reviewer produces an unevidenced concern that should be measured for recurrence rather than chased. For the review itself see code-review-and-quality or skill-library-review; for verifying formal claims with deterministic evidence see adversarial-claims-reviewer.

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Run Karpathy-style autoresearch optimization on any content. Generates 50+ variants, scores with a 5-expert simulated panel, evolves winners through multiple rounds, outputs optimized version + full experiment log. Use when optimizing landing pages, email sequences, ad copy, headlines, form pages, CTA text, or any conversion-focused content. Triggers on "optimize this page", "run autoresearch", "score these variants", "A/B test this copy".

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Use when building games or interactive software in Phaser 3 with TypeScript — scenes, gameplay code, input, Arcade physics, animations, audio, tweens, asset preloading, save systems, performance work, or scaffolding with Vite. Triggers on "Phaser", "Phaser 3", "Phaser.Scene", "Phaser.Game", "Arcade physics", "Matter physics", "tilemap", "Tiled", "GameObject", "Container", "Group", "Vite + Phaser", or any `.ts`/`.js` file in a Phaser project. For game design and balance see game-systems-designer, game-balancer; for game intake see game-design-shaper. For Godot/C# see godot-engineer.

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Breaks work into ordered, parallel-dispatchable tasks with an execution DAG. Output format is consumable by CI matrices and parallel agent runners — each task has a stable ID, declared file writes, conflict edges, and branch suffix. Use when you have a spec, brief, or shaper output and need to decompose it into implementable units. Use when a task feels too large, when scope spans multi-repo or multi-week work, or when parallel execution across multiple agents is on the table.

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Conducts multi-axis code review across correctness, readability, architecture, security, and performance. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Triggers on "review my PR", "review this diff", "code review", "review this changeset", "is this ready to merge", "pre-merge review".

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Use when forensically auditing a Claude Code skill/agent/command/workflow library against RULESET.md by a fixed mechanical protocol — probing every file against the mechanically-checkable rules and reporting CONFORMS / VIOLATES / UNVERIFIABLE / N-A counts with quoted evidence. It casts NO judgment and emits NO pass/fail verdict; counts are the headline. Triggers on "investigate the library", "audit against RULESET", "find every violation", "forensic library audit", "evidence-only check". Not for routing/quality/single-responsibility judgment — use skill-library-review. Not the full sharded sweep — use the audit-library command.

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Use when adversarially reviewing a document that makes formal or technical claims — math derivations, physics papers, statistical analyses, benchmark reports, whitepapers. Inventories every equation and quantitative claim, verifies each AS NAMED in the text (never a paraphrase or a neighboring statement), and classifies VERIFIED / REFUTED / UNVERIFIABLE / VACUOUS. Triggers on "check this paper", "verify these claims", "is this derivation right", "review this proof", "audit this benchmark", "does the math hold up". For source-code review see code-review-and-quality; for skill/agent library audits see skill-library-review; for content quality scoring see content-ops.

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Catalog APIs, persistence models, and message/event payloads into DATA_MODEL.md at the project root. Use after implementation when a diff touches request/response types, schemas, ORM models, queue payloads, or webhook shapes. Triggers on "document data model", "update DATA_MODEL", "catalog API shapes".

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。