「schema」の検索結果

GraphQL API specialist for schema design, resolvers, federation, and performance optimizationUse when "graphql, schema design, resolvers, federation, apollo, relay, dataloader, n+1 problem, graphql security, graphql, api, schema, resolvers, federation, subscriptions, apollo, relay, dataloader" mentioned.

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Database design specialist for schema modeling, query optimization, indexing strategies, and data integrityUse when "database design, schema, indexes, query optimization, migrations, normalization, database scaling, foreign keys, data modeling, database, sql, postgres, mysql, mongodb, schema, indexes, migrations, normalization, optimization" mentioned.

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临床诊断思维 (临床诊断思维 / 临床推理 (Clinical Diagnostic Reasoning) — 医生『怎么想病』的元学科:从症状/体征/检查到诊断结论的认知操作系统,从业者(临床医生/住院医/规培生,尤其全科/急诊/大内科等以未分化主诉为生的科室)、医学生与医学教育者、诊断安全与质量改进研究者、以及做医疗 AI 辅助诊断产品的人的视角。覆盖: (a) 第一性张力 — **直觉模式识别 (System 1: illness scripts 疾病脚本 / pattern recognition / gestalt, 『资深人一眼认出 aunt Minnie』) ⇄ 分析性推理 (System 2: hypothetico-deductive 假设演绎 / Bayesian 概率更新)** 的 dual-process 双过程理论 (Kahneman→Croskerry/Norman 谱系), 资深≠更会分析而是『脚本库更大+校准更好』; 更深层论战 — **『认知去偏可教 (Croskerry: bias awareness / cognitive forcing strategies / diagnostic timeout) ⇄ 偏倚标签是马后炮、知识结构才是主因 (Norman/Sherbino/Monteiro: debiasing 干预 transfer 证据弱, bias 是 hindsight 标签)』** — 本行最核心学术对垒; 『概率思维 (验前概率 × 似然比 → 验后概率, Pauker-Kassirer test/treatment threshold 阈值模型) ⇄ 穷尽式排查 (rule-out everything / 防御性医疗 / VOMIT)』; 『临床 gestalt ⇄ 结构化临床决策规则 (Wells/PERC/HEART)』; 『诊断简约 Occam's razor ⇄ Hickam's dictum (病人可以同时得 N 个病)』; 『床旁体格检查复兴 (Verghese Stanford 25 / McGee 循证体检) ⇄ 影像检验替代床旁』; (b) 方法论正典 — illness script theory (Schmidt/Boshuizen: enabling conditions/fault/consequences 三段结构), problem representation + semantic qualifiers 问题表征与语义限定词 (Bowen NEJM 2006, 把病人翻成 one-liner), hypothetico-deductive model (Elstein 1978《Medical Problem Solving》: 早期假设生成+定向检验), Bayesian 工具箱 (sensitivity/specificity/LR/Fagan nomogram/SnNout-SpPin), threshold model (Pauker-Kassirer NEJM 1975/1980), 认知偏倚分类学 (anchoring/premature closure/availability/confirmation/base-rate neglect/search satisficing/diagnostic momentum — Croskerry 偏倚清单), 去偏与元认知策略 (diagnostic timeout/cognitive forcing/Ely checklist/calibration), schema-based reasoning (Clinical Problem Solvers schemas: 按 pivot 症状走分支), reflective practice 结构化反思 (Mamede/Schmidt), 诊断错误科学 (NAM 2015 报告定义 / Newman-Toker Big Three / Hardeep Singh e-triggers / SAFER Dx 框架); (c) 行业结构与角色 — 医学生→实习/住院医 (晨会 morning report/查房被 pimping/汇报训练)→主治 attending→master clinician (NEJM CPC discussant/晨会大师如 Dhaliwal); 配套生态: 医学教育者 (clinical reasoning curriculum + 评估: script concordance test/key features exam/OSCE), 诊断安全研究者 (SIDM/AHRQ), 诊断辅助与 CDS 工具开发者 (DDx generator/AI); (d) 核心工作流 — 数据采集 (病史为王 + 循证体检 + 针对性检验影像) → 问题表征 (one-liner + semantic qualifiers) → 鉴别诊断生成 (schema / 解剖定位法 / VINDICATE-M 病因筛, 按『常见可能 × 致命不能漏 can't-miss』双轴排序) → 假设定向检验 (按 LR 选检查 / 阈值决策) → working diagnosis + 安全网 (red flags 交代 / test of time / test of treatment) → 反馈校准 (follow-up / M&M / diagnostic timeout); 教学工作流: 晨会渐进披露汇报 / CPC / SNAPPS / one-minute preceptor / virtual morning report; AI 增强工作流 (2023-2026: LLM 鉴别诊断头脑风暴 / OpenEvidence 检索 / ambient scribe 释放认知带宽 + 自动化偏倚 guardrails); (e) 产出物 — one-liner, problem list, prioritized DDx, assessment & plan (按问题分层), 晨会/CPC 汇报, M&M 复盘, 诊断不确定性沟通 (『最可能是 X, 但出现 Y 红旗立刻回来』); (f) 教育与评估 — script concordance test / key feature exam / EPA / 里程碑; 中国语境: 人卫《诊断学》教材 / 执业医师考试 / 规培结业临床思维考核; (g) 争议/批判 — debiasing 之争 (Croskerry vs Norman-Sherbino『knowledge is the cure』, 去偏 RCT 效果弱 / bias 标签不可证伪), 诊断错误率数字之争 (『10-15%』经典估计 / Newman-Toker 79.5 万美国年严重伤害外推方法被质疑 / 尸检符合率), dual-process 二分被批过度简化 (连续谱 / 难以实证分离), 决策规则 vs gestalt (资深 gestalt 常不输 Wells 类规则 / 算法厌恶), vignette 研究外推性 + context/case specificity (推理高度内容绑定不可通用迁移 [Norman/Eva] — 对『教推理通用课』产业的根本批判), AI 辅助诊断 2023-2026 (GPT-4 在 NEJM CPC/vignette 追平或超医生 [Kanjee 2023 JAMA / Goh 2024 JAMA Netw Open『AI alone > physician+AI』悖论] / Google AMIE / OpenEvidence 爆发 vs 自动化偏倚 / 去技能化 / 真实环境验证缺失), 防御性医疗与过度检查 (incidentaloma 瀑布 / VOMIT), 体检衰亡之争, pimping 教学法争议; (h) 流派/思想谱系 — 决策科学/Bayesian 派 (Ledley-Lusted 1959 → Elstein/Kassirer/Sox/Pauker/Eddy → Brush) vs 认知心理/双过程派 (Kahneman-Tversky → Croskerry/Graber) vs 教育认知派 (Schmidt/Boshuizen illness scripts → Norman/Eva/Mamede/Durning 情境认知) vs 诊断安全/系统派 (NAM 2015 / Newman-Toker / Hardeep Singh / Graber-SIDM: 错误=系统×认知共因) vs 床旁临床派 (Osler 传统 → Tierney aphorisms / Verghese / McGee / Dhaliwal / Saint: 病史体检为王 + 刻意练习) vs AI/计算派 (INTERNIST-1/DXplain 专家系统 → Isabel → LLM 世代 Rodman/Topol)。不含: 具体专科治疗方案与手术决策深度 (足踝外科/种植牙等另有 skill), 中医辨证 (另有 skill), EBM 文献批判性评价方法学 (相关但本 skill 聚焦诊断推理本身), 护理诊断体系 (NANDA), 影像/病理知觉型读片训练 (相邻但独立), 精神科 DSM 结构化访谈细节, 医患沟通技巧全集 (只覆盖诊断不确定性沟通), 患者自查/自我诊断指

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现代建筑设计 (从 concept 草图到施工图与现场服务的整套设计流程, 含 BIM / 可持续 / 参数化 / 在地性 模块, 全球语境 + 中国本土实践并重) (modern architecture design — 当代建筑设计 (concept → schematic → DD → CD → CA + sustainability / BIM / parametric / 中外双语 canon, 不含纯室内 / 景观 / 城市规划 / 结构 / MEP, 那些是相邻专业)) Master OS — automated mastery of modern architecture design — 当代建筑设计 (concept → schematic → DD → CD → CA + sustainability / BIM / parametric / 中外双语 canon, 不含纯室内 / 景观 / 城市规划 / 结构 / MEP, 那些是相邻专业): top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on modern architecture design — 当代建筑设计 (concept → schematic → DD → CD → CA + sustainability / BIM / parametric / 中外双语 canon, 不含纯室内 / 景观 / 城市规划 / 结构 / MEP, 那些是相邻专业) problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「建筑设计」「建筑师」「建筑事务所」「设计院」「方案设计」

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Route HugeGraph MCP schema design, validation, and dry-run preview tasks to stable public tools. Use when the user asks to design vertex labels, edge labels, properties, primary keys, indexes, or preview schema operations.

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Use when the user wants schema preparation, event design, selector validation, schema review, or event-spec generation.

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。

Detect, validate, and generate Schema.org structured data. JSON-LD format preferred. Use when user says "schema", "structured data", "rich results", "JSON-LD", or "markup".

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Design database schemas with Prisma/Drizzle, PostgreSQL index strategy (B-tree, GIN, GiST, BRIN, Hash), query optimization (EXPLAIN ANALYZE), migration safety (expand/contract, zero-downtime), and sharding/partitioning. Use when user asks to design schema, create migrations, optimize slow queries, add indexes, choose between SQL/NoSQL, or set up Prisma/Drizzle. Do NOT use for data warehouse dimensional modeling, ETL pipeline design, or non-relational (MongoDB, DynamoDB) schema design.

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Piaget's constructivism, schema theory, and cognitive development as practical tools for curriculum design. Covers assimilation, accommodation, equilibration, the four stages (sensorimotor, preoperational, concrete operational, formal operational), conservation tasks, schema-based reading and problem-solving, and the distinction between developmental readiness and domain-specific expertise. Use when designing age-appropriate material, diagnosing why a learner is not assimilating new content, or building on prior knowledge.

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Emit Postgres.sql and SQLite.sql from a single schema spec so tools work across both drivers without duplicating DDL by hand. Use when designing a schema that needs to support both shared Postgres deployments and zero-config SQLite. Reduces two-file sync burden to a single source edit.

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CatColab Schemas - database schema modeling distinguishing entities (tables) from attributes (columns). Foundation for ACSets (Attributed C-Sets) and AlgebraicJulia data structures.

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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db / dispatch_tracker.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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Use when scraping JavaScript-heavy pages or SPAs, crawling multiple URLs concurrently, extracting structured data with reusable CSS/JSON schemas, or building automated web data pipelines. Wraps the Crawl4AI library (`crwl` CLI and Python SDK) with schema-generation patterns for LLM-free extraction. Triggers on crawl4ai, crwl, scrape JS-heavy site, scrape SPA, headless browser scrape, schema-based extraction, batch crawl, sitemap crawl, web data pipeline. SKIP when a static HTML page can be read with `defuddle` / `fetch-web` — those are faster cold-start and don't need a browser.

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Detect, validate, and generate Schema.org structured data. JSON-LD format preferred. Use when user says "schema", "structured data", "rich results", "JSON-LD", or "markup".

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Design deterministic technical SEO and schema.org guidance for crawlable public pages. Use this skill when the user asks for title and meta description rules, canonical and hreflang tags, JSON-LD schema, NewsArticle, Article, TechArticle, BreadcrumbList, WebSite, Organization, Person, OpenGraph, Twitter cards, sitemap, news-sitemap, RSS, robots.txt, llms.txt, publisher logo, ImageObject, or metadata templates that must match visible content.

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When the user wants to audit, review, or diagnose SEO issues, plan site architecture, or implement schema markup. Use when someone says 'SEO audit', 'technical SEO', 'site architecture', 'schema markup', 'internal linking', 'why isn't my site ranking', 'site health check', 'crawl issues', 'fix my SEO', 'my traffic dropped', 'rankings fell', or 'site not ranking'. Also trigger when someone wants to plan URL structure, design navigation, add structured data, or review any website for search performance. Three modes: Full Audit (comprehensive health check), Architecture (URL structure and internal linking), Schema (JSON-LD structured data). Covers crawlability, indexation, Core Web Vitals, and on-page factors.

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Reorganize label-heavy or netlist-like electronic schematics into human-readable functional diagrams with visible local wiring while preserving proven connectivity. Use for schematic readability correction, overlapping wires or symbols, visually floating connectors or support logic, functional-sheet restructuring, bus presentation, layout annotations, or multi-EDA handoff across KiCad, Altium, EasyEDA, EAGLE/Fusion, gEDA/Lepton, SPICE/netlist, and PDF/image sources.

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"Implement Schema.org structured data markup in JSON-LD format for enhanced search results. Use this skill when the user needs to add rich snippets to web pages, implement FAQ/Product/Article schema, or validate structured data — even if they say 'rich snippets', 'structured data', or 'Google rich results'.".

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Edit the Prisma Next data contract — add models, fields, relations, indexes, enums, value objects (composite types), type aliases, namespaces (Postgres schemas), cross-contract foreign keys (cross-space FK), polymorphic types (`@@discriminator` / `@@base`), use extension namespaces (`pgvector.Vector(...)`, `cipherstash.EncryptedString(...)`), wire `prisma-next.config.ts` with `defineConfig` from the `@prisma-next/<target>/config` façade, and run `prisma-next contract emit`. Use for schema, models, fields, attributes, soft delete, paranoid, scopes, validations, callbacks, prisma schema, PSL, contract.prisma, contract.ts, contract.json, contract.d.ts, façade imports, `@prisma-next/postgres/config`, `@prisma-next/postgres/contract-builder`, `@prisma-next/postgres/control`, `@prisma-next/mongo/config`, `@prisma-next/mongo/contract-builder`, `extensions:`, `extensionPacks`, pgvector, cipherstash, postgis, paradedb, supabase, `@prisma-next/extension-supabase`, `@@control`, control policy, managed, tolerated, external, observed, PN-CLI-4002, PN-CLI-4003, PN-CLI-4011.

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End-to-end SEO operations for B2B SaaS organic visibility. Use this skill when you need keyword research, technical SEO audits, content optimization, link building strategy, international expansion, AI/AEO optimization, schema markup, Core Web Vitals improvements, and organic traffic growth planning. Also triggers on: SEO, keyword research, can we rank for this keyword, which keywords are actually worth it, qualify these keywords, check the SERPs, keyword shortlist, too many keywords, technical SEO, link building, content optimization, international SEO, hreflang, x-default, multilingual site, translated pages not ranking, our German site gets no traffic, language switcher, auto-redirect by country, machine translation SEO, content parity, ccTLD vs subfolder, AI search, AEO, GEO, Core Web Vitals, schema markup, organic traffic, G2 listing, Capterra, TrustRadius, review-platform category page, best software roundup, listicle placement, directory submissions, do we need a Google Business Profile in [country], local SEO with no office, Google Business Profile eligibility, virtual office address SEO, coworking address business profile, business profile suspended, NAP consistency, local citations for SaaS, LocalBusiness schema, server log analysis, log file analysis, what is Googlebot crawling, is Googlebot hitting errors, verify Googlebot, fake Googlebot, crawl budget, do we have a crawl budget problem, Crawl Stats report, new pages not getting crawled.

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Define Malli schemas for commands, events, and queries using defschemas

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Comprehensive SEO analysis for any website or business type. Orchestrates 52 sub-skills (52 active): full site audits, technical SEO (CWV/INP), schema, E-E-A-T content quality, images, sitemaps, GEO for AI Overviews, llms.txt generation, AI crawler audit, plus live GSC and Ahrefs MCP data. GSC: overview, drops, opportunities, brand-vs-nonbrand, cannibalization, compare, content-decay, index-issues, new-keywords. Ahrefs: overview, backlinks, keywords, competitors, content-gap, broken-links, new-links, anchor-analysis, dr-history, top-pages. Cross-MCP: serp, content-brief, brand-radar, site-audit-pro, report. Local: log-analysis, ai-content-check, internal-links, local, migration-check, obsidian-kb. AI Readability: llms-txt, robots-ai. Performance: lighthouse-audit, core-web-vitals, page-experience. Quality & AI Search: rich-results, ai-optimization, eeat-audit, helpful-content. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "structured data", "GSC", "Ahrefs", "backlinks", "keywords", "search console", "domain rating", "local SEO", "migration", "lighthouse", "pagespeed", "LCP", "INP", "CLS", "page experience", "interstitials", "mobile friendly", "rich results", "rich snippets", "schema eligibility", "AI optimization", "AI search readiness", "EEAT", "trust signals", "helpful content", "people-first", "content quality gate".

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Analyze existing KiCad projects, schematics, PCB layouts, Gerbers, netlists, and PDF reference schematics. Use when files such as .kicad_sch, .kicad_pcb, .kicad_pro, or Gerbers are supplied and the user wants review, debugging, net tracing, ERC/DRC/DFM, schematic-to-PCB comparison, or pre-fabrication checks. Do not use to create a new design from requirements or for standalone sourcing and ordering.

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