「sso」の検索結果

Firebase gives you a complete backend in minutes - auth, database, storage, functions, hosting. But the ease of setup hides real complexity. Security rules are your last line of defense, and they're often wrong. Firestore queries are limited, and you learn this after you've designed your data model. This skill covers Firebase Authentication, Firestore, Realtime Database, Cloud Functions, Cloud Storage, and Firebase Hosting. Key insight: Firebase is optimized for read-heavy, denormalized data. If you're thinking relationally, you're thinking wrong. 2025 lesson: Firestore pricing can surprise you. Reads are cheap until they're not. A poorly designed listener can cost more than a dedicated database. Plan your data model for your query patterns, not your data relationships. Use when "firebase, firestore, firebase auth, cloud functions, firebase storage, realtime database, firebase hosting, firebase emulator, security rules, firebase admin, firebase, firestore, cloud-functions, serverless, backend, realtime, authentication, google-cloud" mentioned.

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Use when integrating Plaid, Stripe, payment processors, or financial APIs - covers account linking, payment processing, KYC/AML compliance, and webhook handlingUse when ", " mentioned.

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Docker makes "works on my machine" a deployment strategy. Package your app with its dependencies, run it anywhere. But Docker's simplicity hides real complexity. A naive Dockerfile can be 10x larger and slower than it needs to be. This skill covers Dockerfile optimization, multi-stage builds, Docker Compose for development, security hardening, and production patterns. Key insight: your Dockerfile is code. Review it, optimize it, version it. 2025 lesson: Containers aren't VMs. The patterns that work for VMs (install everything, big base images) are anti-patterns for containers. Think small, think immutable, think layers. Use when "docker, dockerfile, container, docker compose, docker build, containerize, docker image, multi-stage build, docker network, docker volume, docker, containers, devops, deployment, infrastructure, security, optimization" mentioned.

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Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% by step 10. Build for reliability first, autonomy second. 2025 lesson: The winners are constrained, domain-specific agents with clear boundaries, not "autonomous everything." Treat AI outputs as proposals, not truth. Use when "autonomous agent, autogpt, babyagi, self-prompting, goal decomposition, react pattern, agent loop, self-correcting agent, reflection agent, langgraph, agentic ai, agent planning, autonomous, agents, langgraph, react, planning, reflection, guardrails, reliability, checkpointing" mentioned.

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Angular is opinionated and comprehensive - it gives you everything: routing, forms, HTTP, dependency injection, testing. The learning curve is steep, but once you're in, you move fast. The structure it enforces is why enterprises love it. This skill covers Angular 17+, standalone components, signals, the new control flow syntax, and modern Angular patterns. Key insight: Angular's power is in its DI system and RxJS integration. Master those, and everything else follows. 2025 lesson: Standalone components are the future. NgModules aren't going away, but new projects should start standalone. Signals are Angular's answer to fine-grained reactivity - learn them. Use when "angular, angular component, angular service, angular routing, angular forms, rxjs, ngrx, angular signals, standalone component, angular ssr, angular, typescript, frontend, spa, enterprise, rxjs, signals, standalone" mentioned.

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Accessibility isn't a feature - it's a fundamental quality of good software. 1 in 4 adults has a disability. Many more have temporary impairments or situational limitations. Your users include people who can't see, can't hear, can't use a mouse, or can't process information the way you do. This skill covers WCAG guidelines, ARIA patterns, keyboard navigation, screen reader compatibility, and automated testing. Key insight: accessible code is better code. The constraints of accessibility lead to simpler, more semantic, more maintainable implementations. 2025 lesson: Accessibility lawsuits are at an all-time high. "We'll add it later" is both ethically wrong and legally risky. Start accessible, stay accessible. Use when "accessibility, a11y, wcag, aria, screen reader, keyboard navigation, focus trap, alt text, color contrast, skip link, accessible, accessibility, a11y, wcag, aria, screen-reader, keyboard, inclusive, semantic-html" mentioned.

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健身私教 — 为客户设计、指导和推进个性化训练方案的专业工艺, 有别于团课教练、物理治疗师或运动队教练: (a) 训练方案设计与周期化 (线性 / 波动 / 板块周期化 Bompa & Haff; NSCA《力量训练与体能训练精要》行业圣经; Schoenfeld 肌肥大机制; Helms/Valdez/Morgan 肌肉与力量金字塔; 共轭训练法 Simmons/Westside; Starting Strength 线性渐进 Rippetoe; Renaissance Periodization 训练量地标 Israetel); (b) 动作评估与筛查 (FMS 功能性动作筛查 Gray Cook; NASM CEx 纠正性训练连续体 抑制-拉伸-激活-整合; 关节逐级方法 Cook/Boyle; 姿势与代偿模式识别; PAR-Q+ 与 ACSM 运动前筛查指南); (c) 教学与指令 (外部 vs 内部注意焦点 Wulf; 差异化学习 Schöllhorn; 约束导向方法 Davids/Renshaw; RIR/RPE 自动调节 Zourdos/Helms; 动机访谈在健身中的应用 Rollnick/Miller); (d) 营养指导的执业边界 (宏量营养素周期化; Precision Nutrition / ISSN 立场声明的循证建议; 边界: 私教提供一般性指导, 医学营养治疗需 RD/RDN 资质; 能量可用性与 RED-S Mountjoy IOC 共识); (e) 商业与客户管理 (客户留存与方案依从; 咨询与销售伦理; 线上教练平台与规模化 Goodman PTDC; 方案交付工具 TrueCoach/Trainerize/TrainHeroic; 课时定价模型; 独立教练 vs 健身房雇员); (f) 专项方向 (运动表现 CSCS; 纠正性训练 CES; 老年健身 SFN; 产前产后; 青少年 YSCA; 适应性 / 无障碍健身; 健美 / 形体; 力量举; 耐力运动 S&C)。诚实处理: 兄弟科学 vs 循证之争, 补剂行业利益冲突, 合成代谢激素使用现状 (诚实但不推广: 匿名调查约 30% 有经验男性健身者使用过 — 业内估, Kanayama/Pope/Hudson 记录健康风险, WADA 禁用清单用于竞技语境), 体型焦虑与进食障碍风险 (男性私教肌肉变形症, 正食症倾向, NEDA 负责任语言指南), 健身房掠夺性销售 (高压推销、误导性对比照、长约锁定), 执业边界违规 (私教诊断伤病或超范围开饮食处方), 线上教练认证造假 (周末速成、未经认可的认证)。不含: 物理治疗 / 康复治疗 (持照医疗职业), 不含: 团课教练 (Les Mills/Zumba/CrossFit 分馆教练 — 相邻但不同), 不含: 精英竞技运动教练 (团队项目周期化, 不同职业路径), 不含: 营养作为主业 (临床营养学需单独资质)。 (Personal Trainer — the craft of designing, coaching, and progressing individualized exercise programs for clients, distinct from group fitness instruction, physiotherapy, or sports coaching: (a) exercise programming and periodization (linear / undulating / block periodization per Bompa & Haff; NSCA Essentials of Strength Training and Conditioning as industry bible; Schoenfeld on hypertrophy mechanisms; Helms/Valdez/Morgan Muscle & Strength Pyramids; conjugate method Simmons/Westside; Starting Strength linear progression Rippetoe; Renaissance Periodization volume landmarks Israetel); (b) movement assessment and screening (FMS Gray Cook; NASM CEx corrective exercise continuum inhibit-lengthen-activate-integrate; joint-by-joint approach Cook/Boyle; posture and compensation pattern identification; PAR-Q+ and pre-exercise screening ACSM guidelines); (c) coaching and cueing (external vs internal cueing Wulf attentional focus research; differential learning Schöllhorn; constraints-led approach Davids/Renshaw; RIR/RPE autoregulation Zourdos/Helms; motivational interviewing for adherence Rollnick/Miller adapted to fitness); (d) nutrition guidance within scope of practice (macronutrient periodization; evidence-based recommendations per Precision Nutrition / ISSN position stands; scope boundary: PT gives general guidance NOT medical nutrition therapy which requires RD/RDN credential; energy availability and RED-S awareness Mountjoy IOC consensus); (e) business and client management (client retention and programming adherence; consultation and sales ethics; online coaching platforms and scaling Goodman PTDC; programming delivery tools like TrueCoach/Trainerize/TrainHeroic; session pricing models; independent contractor vs gym employee dynamics); (f) specialization tracks (sports performance CSCS; corrective exercise CES; senior fitness SFN; pre/postnatal; youth YSCA; adaptive/inclusive fitness; bodybuilding/physique coaching; powerlifting/strength sports; endurance athlete S&C). Evidence-based practice as the core ethos: Schoenfeld/Krieger meta-analyses on volume-response, Helms systematic reviews on protein/resistance training, Brad Schoenfeld's MASS journal bridging research to practice, Menno Henselmans and Eric Helms as practitioner-researchers, Greg Nuckols Stronger By Science as translation layer. Chinese fitness industry context: rapid growth of personal training in commercial gyms (Keep/Lefit/Megafit chains), NSCA-CPT and ACE-CPT as dominant certifications alongside local CSFA (China Sport and Fitness Association) credential, '体适能' (physical fitness) as formal term, online coaching boom post-COVID, PT business models in tier 1-3 cities diverge sharply. Honest treatment of: bro science vs evidence-based d

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游戏设计 (Game Design) — 设计游戏的规则 / 系统 / 机制 / 体验 的从业者认知操作系统 (以电子游戏为主, 含桌游 / 卡牌 / 棋盘游戏): 决定「玩家做什么、为什么有意义、每一刻的体验如何」的学科 —— 区别于游戏程序 (引擎 / 代码)、游戏美术 (视觉 / 音频)、游戏制作 (排期 / 预算 / 团队)。覆盖 (a) 核心设计理论与框架 (MDA 机制-动态-美学 Hunicke/LeBlanc/Zubek + Schell 的「透镜」+ Koster「乐趣即学习」理论 + Sid Meier「一连串有趣的决策」+ Salen & Zimmerman「有意义的游玩」/「二阶设计」/「魔法圈」+ Costikyan 论不确定性 + Suits/Huizinga 游戏哲学), (b) 系统与机制设计 (核心循环 + 游戏经济 sink/source/产出-消耗 + 正负反馈环 + 资源与成长系统 + 涌现 vs 脚本 Will Wright「可能性空间」+ Machinations 经济建模 Dormans + 支配 / 退化策略 + 正交设计 Garfield), (c) 关卡与遭遇设计 (灰盒 blockout + 节奏与张力 + 预告 telegraphing + 主线 vs 探索 + 环境叙事 + 锁钥 gating + 难度曲线), (d) 游戏手感与「juice」(Steve Swink《Game Feel》+ 即时响应 + 屏震 / 反馈 / 打磨 + 输入与镜头 + 「手感」是设计出来的不是附带的), (e) 玩家心理与 UX (Celia Hodent《The Gamer's Brain》+ 心流通道 挑战 vs 技能 Csikszentmihalyi/陈星汉 Jenova Chen + Bartle 玩家类型 + 动机与奖励节奏 + 新手引导 FTUE / 教学化 + 认知负荷 + 无障碍), (f) 平衡与调优 (Ian Schreiber《Game Balance》+ 对称 / 非对称 + 动态难度 DDA + 传递 / 非传递平衡 + nerf/buff + 消除支配策略 + 测试驱动调优), (g) 叙事与任务设计 (ludonarrative 失调 / 和谐 + 环境与系统叙事 + 分支 vs 线性 + Amy Hennig 角色驱动 + 任务结构), (h) 以玩家为中心的迭代流程 (Tracy Fullerton《Game Design Workshop》playcentric + 纸面原型 + 垂直切片 + 测试协议「看而不说 / 你不是你的玩家」+ 快速迭代 + game jam), (i) 类型与形态工艺 (roguelike/roguelite 与程序生成 Derek Yu + 平台跳跃 + RPG 系统 + 策略 4X + 解谜设计 Jonathan Blow + 多人 / PvP 平衡 + 桌游 / 卡牌设计 Reiner Knizia/Richard Garfield/Brenda Romero), (j) F2P / 长线运营 / 商业化设计 (核心 / 元 / 经济循环 + 抽卡 gacha / 开箱 loot box / 战令 battle pass 机制 + 留存 D1/D7/D30 + 转化 + 鲸鱼 + live ops 内容节奏 —— 并诚实处理掠夺式暗黑模式 / 强迫循环 / 剥削式商业化的伦理), (k) 设计师角色与工艺职业 (系统 / 关卡 / 叙事 / UX 设计师之分 + 通才 vs 专才 + 独立作者 vs 3A 团队 + 设计文档 + 传达设计意图 + GDC 工艺社区)。跨 3A / 独立 / 手游 F2P / 桌游。不含 游戏程序 / 引擎 (Unity/Unreal 编码 / 图形 / 网络同步) / 游戏美术 / 动画 / 音频 / 游戏制作 / 项目管理 / 排期 / QA / 游戏作为生意 / 发行 / 市场 / 电竞运营为终点 / 泛泛「我想做游戏」的 game-dev 教程 —— 本 skill 是「设计」学科: 规则 / 系统 / 机制 / 体验。 (Game Design — the cognitive operating system of practitioners who design the rules, systems, mechanics, and experiences of games (video games primarily, plus tabletop/board/card games): the discipline of deciding WHAT the player does, WHY it is meaningful, and HOW the moment-to-moment experience feels — distinct from game programming (builds the engine/code), game art (visuals/audio), and game production (schedule/budget/team). Covers (a) core design theory & frameworks (MDA Mechanics-Dynamics-Aesthetics Hunicke/LeBlanc/Zubek, Schell's Lenses, Koster's theory of fun = learning, Sid Meier 'a series of interesting decisions', Salen & Zimmerman 'meaningful play'/'second-order design'/'magic circle', Costikyan on uncertainty, Suits/Huizinga play philosophy), (b) systems & mechanics design (core loops, game economy sink/source/faucet-drain, feedback loops positive/negative, resource & progression systems, emergence vs scripting Will Wright 'possibility space', Machinations economy modeling Dormans, dominant/degenerate strategy, orthogonal design Garfield), (c) level & encounter design (blockout/greybox, pacing & tension, telegraphing, critical path vs exploration, environmental storytelling, gating & lock-and-key, difficulty curve), (d) game feel & juice (Steve Swink 'Game Feel', moment-to-moment responsiveness, screenshake/feedback/polish, input & camera, the 'feel' is designed not incidental), (e) player psychology & UX (Celia Hodent 'The Gamer's Brain', flow channel challenge-vs-skill Csikszentmihalyi/Jenova Chen, Bartle player types, motivation & reward schedules, onboarding/FTUE/tutorialization, cognitive load, accessibility), (f) balancing & tuning (Ian Schreiber 'Game Balance', symmetry/asymmetry, dynamic difficulty adjustment DDA, transitive/intransitive balance, nerf/buff, dominant strategy elimination, playtesting-driven tuning), (g) narrative & quest design (ludonarrative dissonance/harmony, environmental & systemic storytelling, branching vs linear, Amy Hennig character-driven, quest structure), (h) player-centric iterative process (Tracy Fullerton 'Game Design Workshop' playcentric design, paper prototyping, vertical slice, playtesting protocol 'watch don't talk / you are not your play

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Use when adding, moving, or removing images, sprites, text, or video on the Pixi'VN game canvas, or when applying or creating transitions (dissolve, fade, move, zoom, push, wipe, iris, split, flash, blur, pixelate, or a custom one built on `canvas.animate`/`filters.animate`), shake/animation effects, or ticker-based animations built on PixiJS. Covers the `canvas` singleton exported from `@drincs/pixi-vn`. For UI layers (HTML or PixiJS) mounted on top of the canvas, see `pixi-vn-ui` instead.

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Dùng khi viết hoặc sửa prompt tạo video/ảnh AI (Veo 3, Google Flow, Kling, Runway, Sora, Midjourney, Hailuo, Luma): từ vựng chuẩn về góc máy, chuyển động camera, ánh sáng, bố cục, phong cách, màu, cảm xúc công thức ghép prompt, và bài học thực chiến về lỗi model AI hay gặp. Use when writing or fixing AI video/image prompts — cinematic camera angles, camera movement, lighting, composition, style, color grading, mood, a prompt formula, and real-world lessons on common AI video model failures.

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Use when the user wants to teach / learn an English word as a video — turn a single English word into a self-contained HLS "supercut" lesson built from the mira video base. Stitches every season2 clip where the word is spoken (via the search-app API) into one .m3u8, prepended with a Claude-written bilingual word-intro card (word + IPA + 中文 gloss + usage, Volcano TTS) and appended with a 关注王建硕 CTA card. No MP4 burn. Triggers — "teach <word>", "讲讲 <word>", "学英语 <word>", "把 <word> 做成视频", "/wjs-teaching-english <word>".

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Applies the reasoning of Pieter Abbeel, robotics and reinforcement learning expert, UC Berkeley professor, and co-founder of Covariant. Use this skill whenever you are designing AI systems, tackling Sim2Real transfer, deploying machine learning in the physical world, or evaluating reinforcement learning architectures. Trigger this skill for questions about domain randomization, reward design, bootstrapping real-world AI, robotics hardware assumptions, or shifting from hard-coded rules to data-driven deep learning. It helps ground theoretical AI in physical embodiment and pragmatic deployment.

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Reach for this skill whenever you are discussing reinforcement learning, agentic AI systems, AI alignment, continual learning, or the philosophical limits of large language models. This skill channels the thinking of Richard S. Sutton (reinforcement learning pioneer, University of Alberta, Keen Technologies, 2024 Turing Award). Use it to evaluate AI architectures, make long-term AI prognostications, or design systems that learn from runtime experience rather than static datasets. Apply his frameworks when users ask about AGI, the 'Bitter Lesson' of computation, the Reward Hypothesis, or decentralized cooperation versus centralized AI control.

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Applies the reasoning of Stuart Russell, AI safety expert, UC Berkeley professor, and co-author of 'Artificial Intelligence: A Modern Approach'. Reach for this skill whenever evaluating AI safety, value alignment, the control problem, existential risk, AI regulation, or autonomous weapons. Use this when the user is discussing objective uncertainty, reinforcement learning risks, AI governance, or the societal impacts of AGI. Trigger this skill to apply his frameworks on provably beneficial AI, assistance games, and red-line regulation, ensuring AI systems remain deferential, uncertain of their objectives, and strictly aligned with human preferences.

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Use this skill when reasoning about deep tech commercialization, biomedical engineering, drug delivery, material design, or overcoming institutional skepticism. Robert Langer, MIT professor and pioneer of drug delivery systems, approaches problems through first-principles engineering, interdisciplinary convergence, and relentless perseverance against consensus. Trigger this skill whenever the user is evaluating high-risk/high-reward research, deciding between incremental vs. paradigm-shifting impact, spinning out academic discoveries into startups, or designing physical/biological systems from scratch. Apply his frameworks to navigate patenting, funding, and translating lab science into real-world impact.

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Applies the analytical and therapeutic philosophy of Ludwig Wittgenstein, 20th-century philosopher of language (Tractatus / Philosophical Investigations). Use this skill when the user is stuck in conceptual confusion, debating semantics, trapped by abstract definitions, or trying to solve a problem that is actually just a linguistic misunderstanding. Trigger this for topics involving the limits of language, meaning as use, logical clarification, or when the user is over-theorizing instead of looking at practical applications. It helps dissolve 'fly-bottle' traps by examining how words are actually used in context.

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Specialized visual and multimedia processing tools. Use this skill whenever a task involves complex visual content — UI mockups, dense screenshots, design images, charts, artwork — where precise details like spacing, hex colors, font sizes, and component hierarchy need to be extracted accurately. Also use for: reviewing or auditing existing UI against designs, comparing screenshots for visual regressions, transcribing audio/video, extracting data from PDFs with complex layouts, and generating images. Trigger whenever the user wants to implement from a design, review or compare UI screenshots, analyze visual details precisely, describe artwork or aesthetic content, or process any media file (audio, video, PDF).

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Programmatic security management in Neo4j — RBAC/ABAC, user lifecycle (CREATE/ALTER/DROP USER), role lifecycle (CREATE/GRANT ROLE/DROP ROLE), privilege grants and denies (GRANT/DENY/REVOKE on graph, database, DBMS), property-level access control, sub-graph access control, SHOW PRIVILEGES inspection, and auth provider config reference (LDAP, OIDC/SSO). Use when an agent needs to manage users, roles, or privileges programmatically via Cypher on the system database. Does NOT handle Cypher query writing — use neo4j-cypher-skill. Does NOT handle cluster ops or backups — use neo4j-cli-tools-skill. Property-level security and ABAC require Enterprise Edition.

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Neo4j Visualization Library (NVL) — framework-agnostic graph rendering for the browser. Covers @neo4j-nvl/base (NVL class, nodes/relationships, Canvas vs WebGL renderer), @neo4j-nvl/interaction-handlers (ZoomInteraction, PanInteraction, DragNodeInteraction, ClickInteraction, HoverInteraction, BoxSelectInteraction, LassoInteraction, KeyboardInteraction), and @neo4j-nvl/react (InteractiveNvlWrapper, BasicNvlWrapper, StaticPictureWrapper). Use when rendering a Neo4j graph in a browser, feeding driver results through nvlResultTransformer, choosing Canvas vs WebGL, wiring node/relationship click/hover/drag handlers, or embedding NVL in React, Vite, or vanilla JS apps. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle driver lifecycle, sessions, or executeQuery setup — use neo4j-driver-javascript-skill. Does NOT handle GraphVisualization/Needle default embed — use @neo4j-ndl/react.

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Implement authentication and authorization with OWASP Top 10 standards, OAuth 2.0 + OIDC, WebAuthn/Passkeys, session management, and RBAC/ABAC. Use when user asks to implement login, signup, authentication, authorization, JWT, OAuth, SSO, passkeys, MFA, or role-based access. Do NOT use for API key management (use api-forge), encryption at rest, or network-level security (firewalls, WAF).

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Reescreve textos em português brasileiro para soarem mais humanos e naturais, reduzindo padrões típicos de escrita gerada por IA sem alterar fatos, argumento ou intenção. Use quando o texto em PT-BR parecer genérico, burocrático ou gerado por IA, ou quando o usuário pedir para "humanizar", "dar vida", "tirar cara de IA", "remover AI slop" ou "reescrever com voz". Use também para ESCREVER DO ZERO em português qualquer texto que uma pessoa vai assinar ou publicar (post, artigo, e-mail, proposta, release, README, bio, descrição de produto): nesse caso a lista de padrões funciona como filtro de saída. Para textos em inglês, use a skill-irmã `human-ai`. Também trabalha a partir de notas e transcrições do autor e faz perguntas pontuais quando faltam dados essenciais.

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Distils repeating patterns from session logs and lessons.md into draft skill files. Run after ≥10 sessions to extract durable knowledge. Output: draft skills/ files + promotion report.

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A multi-day digest of the user's own coding-agent sessions — sessions per day and project, most-edited files, and every lesson Cognee distilled into the knowledge graph in that window. Use only when the user explicitly asks for a weekly digest, a retro, a recap or report of their recent sessions, or asks for the `cognee-digest` skill by name. Not for questions about code or the current task.

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A dated chronology of one topic across the user's recorded coding-agent sessions — the lessons the graph learned about it and the prompts that named it, oldest first. Use only when the user explicitly asks for the history or timeline of a topic across their sessions ("how did X evolve", "when did we first discuss X") or asks for the `cognee-timeline` skill by name. Not for questions about code or the current task.

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