475건 · 관련도순
Build and troubleshoot C#/.NET MCP servers that expose tools and information to AI agents. Guidance targets the official 2.x SDK and covers transport setup, authentication, interactive features, basic clients, and migration issues caused by changed defaults.
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Provides guidance for retrieving China A-share prices and trading volumes through the TDX protocol. The source is currently retired from automatic routing because servers stopped responding, with explicit selection retained for possible future recovery.
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Review personal data handling against GDPR requirements, covering processing records, legal grounds, individual rights, breach procedures, and international transfers. Produce findings by article and a prioritized improvement roadmap with responsibilities, estimated costs, and timelines.
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Automate X / Twitter posts, image uploads, replies, searches, and deletions through browser tools. Includes checks for disabled send buttons, recovery steps for editor problems, and workflows for avoiding duplicate replies.
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Automate LinkedIn messages, connection acceptance, and feed posts with practical browser workflows. The skill explains visual targeting, image uploads, delivery checks, and when to stop if login prompts or account restrictions appear.
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Organize AI agent security findings using the ten OWASP ASI risk categories. Map issues such as leaked credentials or unauthorized tool calls to category IDs, and assign severity levels with suggested remediation timeframes.
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Prepare .NET projects for Native AOT, compilation before execution, and trimming, which removes unused code. Use build warnings to guide type annotations, reflection changes, and source-generated JSON serialization, then check all target frameworks.
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Create a shareable TRES Finance Transactions link filtered by dates, wallets, assets, amounts, and other requested conditions. The skill checks filter values and URL formatting so customers or colleagues can reopen the specified view.
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YOLO 2026 — state-of-the-art real-time object detection
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California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA) compliance advisor — business threshold analysis, consumer rights fulfillment (access, delete, correct, opt-out of sale/sharing, limit SPI, ADMT opt-out), privacy notice drafting, service provider vs. contractor vs. third-party classification, sensitive personal information (SPI) handling, data minimization, opt-out mechanisms (including GPC), cybersecurity audits and risk assessments (live since Jan 1, 2026), ADMT obligations (effective 2026, deadline Jan 1, 2027), CPPA enforcement (Disney $2.75M, PlayOn $1.1M, Ford $375K), penalty exposure, GDPR comparison, and gap assessments for businesses operating in or targeting California residents.
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Expert TISAX (Trusted Information Security Assessment Exchange) advisor for the automotive supply chain — the ENX/VDA assessment regime that OEMs like VW, BMW, and Mercedes-Benz require from suppliers and service providers. Covers the VDA ISA 6 catalogue (current through 2026) and the ISA2027 transition (published July 1, 2026; mandatory for assessments ordered from January 1, 2027), assessment levels AL1/AL2/AL3, all 12 assessment objectives/labels (Confidential, Strictly Confidential, High/Very High Availability, Proto Parts/Vehicles, Test Vehicles, Proto Events, Data, Special Data), maturity scoring (0–5, target 3, cutback rules), the ENX portal process, scoping, audit-provider selection, corrective action plans and the 9-month window, 3-year label validity, and ISO 27001 mapping. Use for any TISAX, VDA ISA, ENX, automotive information-security assessment, prototype protection, or OEM supplier-security requirement question — gap assessments, label selection, readiness, and audit prep.
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California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA) compliance advisor — business threshold analysis, consumer rights fulfillment (access, delete, correct, opt-out of sale/sharing, limit SPI, ADMT opt-out), privacy notice drafting, service provider vs. contractor vs. third-party classification, sensitive personal information (SPI) handling, data minimization, opt-out mechanisms (including GPC), cybersecurity audits and risk assessments (live since Jan 1, 2026), ADMT obligations (effective 2026, deadline Jan 1, 2027), CPPA enforcement (Disney $2.75M, PlayOn $1.1M, Ford $375K), penalty exposure, GDPR comparison, and gap assessments for businesses operating in or targeting California residents.
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Reviews code for security vulnerabilities and guides secure implementation using OWASP Top 10:2025, ASVS 5.0, the OWASP Top 10 for LLM Applications (2026), and the OWASP Top 10 for Agentic Applications (2026). Use when reviewing code or a diff for security issues, implementing authentication, authorization, sessions, or cryptography, handling untrusted input, files, or URLs, hardening config, dependencies, or CI, or building LLM and AI agent features.
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Kentucky Consumer Privacy Protection Act (KPPA) compliance. Effective January 1, 2026. Covers consumer rights, controller thresholds at 100,000 consumers, sensitive data processing consent, cure period provisions, and AG enforcement framework.
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想法群聊室 — 调研员角色。被 idea-team 主编排器调用，或用户单独说"调研一下 X"、"X 的现状/竞品/数据"、"找 2026 数据"、"事实底"时触发。**用 WebSearch 拉真实 2026 数据、列竞品、引来源——只给事实，不评判，不建议**。Do NOT use when 用户要评价想法好坏（那是反方）、或要跨界启示（那是类比者）、或已有 PRD 在跑（不需要这种调研）。插件内 skill 会由 `idea-coach` namespace 路由；catalog 用户直接按 skill 名调用。
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為使用者產生高品質的 AI 生圖、生影片、生音樂提示詞，並在需要時透過瀏覽器自動化實際送到目標平台。涵蓋 OiiOii、Kling 3.0/O-series、Seedance 2.0/2.5、Suno v5.5、Seedream 5.0/4.0、Vidu Q3、Midjourney V8.1、Flux 1.1 Pro / Kontext、Runway Gen-4.5 / Aleph、Google Veo 3.1、Ideogram 3、Nano Banana Pro、Stable Diffusion 3.5（⚠️ OpenAI Sora 2 已於 2026-04-26 停運，API 撐到 2026-09-24，預設改推 Runway/Veo/Kling）。只要使用者提到「AI 生圖」「AI 影片」「AI 音樂」「做 MV」「做 storyboard」「寫 prompt 給 XXX」「我想用 Kling/Suno/Midjourney/Runway/Veo...」「幫我操作 OiiOii / 即夢 / 可靈」「txt2img / img2video / 文生圖 / 文生影片 / 圖生影片」「角色一致性」「多鏡頭分鏡」「運鏡」「結果有瑕疵 / 不夠精緻 / 怎麼修」，或任何跟上述平台或影像/影片/音樂生成工作流相關的任務，都要用這個 skill。即使他們沒講明平台，只要任務是要餵給某個生成模型的 prompt，就用這個 skill 幫他們選對的平台、寫對的格式。
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生成一份对外可分享、脱敏的 AI-Native 开发者 README。 量化展示我对 Claude Code + Codex CLI + Kiro (AWS) + Trae (ByteDance) + Gemini Antigravity (Google) + Cursor 的使用深度、AI 协作风格、 项目与领域分布、兴趣主题，以及与 GitHub 提交的产出关联。 Trigger when the user says: "生成我的 AI 档案" / "做一份 AI-native README" / "分析我的 Claude / Codex / Kiro / Trae / Antigravity / Cursor 使用情况" / "总结我的 AI 使用" / "生成 AI 月度报告" / "按月份分析我的 AI 编码" / "分析 2026-05 的 AI 使用" / "build my AI usage profile" / "build my monthly AI coding report" / "analyze my AI usage for May 2026" / "summarize my Claude / Codex / Kiro / Trae / Antigravity / Cursor history" / "生成开发者画像". 全程本地、只读、默认匿名、不上传任何数据。
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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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Create and manage Neo4j vector indexes, run vector similarity search (ANN/kNN), store embeddings on nodes or relationships, use SEARCH clause (Neo4j 2026.01+, preferred) or db.index.vector.queryNodes() procedure (deprecated 2026.04, still works on 2025.x), configure HNSW and quantization options, pick similarity function and embedding provider dimensions, and batch-update embeddings. Use when tasks involve CREATE VECTOR INDEX, vector.dimensions, cosine/euclidean search, embedding ingestion pipelines, semantic or structural nearest-neighbor lookup, or hybrid search (vector + fulltext, multiple vector sources, or graph-derived scores). Does NOT handle GraphRAG retrieval_query graph traversal — use neo4j-graphrag-skill. Does NOT handle fulltext-only/keyword-only search — use neo4j-cypher-skill. Does NOT compute GDS graph embeddings (FastRP, Node2Vec) — use neo4j-gds-skill.
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Expert guide for late-2026 frontier AI models — Google Gemini 4 Pro & Project Astra, Anthropic Claude 5.1 (Fable/Mythos), and Enterprise Frontier Safeguards (EFS) / Panduan ahli model AI frontier akhir-2026 — Google Gemini 4 Pro & Project Astra, Anthropic Claude 5.1 (Fable/Mythos), dan Enterprise Frontier Safeguards (EFS).
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Expert guide for cutting-edge Native CSS (2026 Standard) — CSS Anchor Positioning, @starting-style, View Transitions Level 2, Container Queries, and :has() / Panduan ahli fitur CSS native modern 2026.
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Despliega soluciones de IA para insurance claims automation con arquitectura modular, metricas auditables y decisiones alineadas al contexto del dominio.
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Expert legal research agent for finding and scraping expungement data state by state. Knows authoritative sources, URL patterns, Firecrawl configuration, and 2026 legal landscape. Activate on "find expungement data", "scrape state laws", "legal research", "court URLs", "statute sources", "Clean Slate laws", "automatic expungement research". NOT for interpreting laws (use national-expungement-expert), building UI, or legal advice.
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Comprehensive 2026 SEO audit covering classic technical SEO (crawl, render, index, Core Web Vitals with INP), on-page (titles, meta, headings, internal linking), content (topical authority, entity density).
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