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招聘与猎头 (招聘与猎头 (Recruiting & Executive Search) — 面向甲方招聘负责人/HR 与市场化猎头顾问「双侧视角」的『把一个模糊的用人需求，变成一个来得了、干得好、留得住的人』的判断体系；不是候选人一侧的求职与简历面经（那是 job-hunting-coach 的范围），也不是薪酬绩效/员工关系/组织发展的泛 HR 全模块，更不是劳动法条文解读。覆盖：(a) 第一性张力 —— 这行的核心世界观分歧：**需求诊断优先 ⇄ 快速供给优先**（用人经理提来的岗位需求几乎总是一张愿望清单，资深招聘先开 intake 会把『必须有』与『最好有』拆开、把画像逼成可证伪的成功标准；但按成单计酬的猎头把诊断时间压不进单价里，于是行业里同时存在『先诊断再搜寻』和『先扔简历再说』两种作业习惯）；**结构化面试 ⇄ 看人的直觉**（工业与组织心理学近一个世纪的效度元分析一致指向：结构化面试、工作样本、认知能力测验的预测效度明显高于非结构化面谈与经验年限，但一线用人经理绝大多数仍相信自己聊两句就能看准人——这是本行最大的知行落差，也是所有循证招聘流派的出发点；顺带一提，业内长期奉为圭臬的 Schmidt-Hunter 效度排序近年被重新校正，工作样本的效度被下调，这场修正本身就是本行必须如实呈现的争议）；**能力素质 ⇄ 文化匹配**（culture fit 既是最常被写在拒信里的理由，也是被批评得最凶的偏见外壳，Google 一派主张改口叫 culture add，看的是这个人补上了团队缺的东西，而不是像不像我们）；**主动寻访 sourcing ⇄ 被动投递漏斗**（高端与稀缺技能岗只有 outbound 人才地图一条路；量大岗位靠渠道效率、转化率与自动化，两条路的技能树几乎不重叠）；**人才地图是资产 ⇄ 人才地图是浪费**（保留制猎头把 mapping 当交付物的一部分，成功付费猎头认为地图做完单子已经黄了）；**保留制 retained ⇄ 成功付费 contingency**（按阶段预付、独家、深度地图 vs 多家赛马、入职才收钱、速度压倒深度；两种商业模式塑造出两种截然不同的作业节奏、候选人对待方式与职业道德边界，比如 off-limits 不挖回自己安置过的人）；**内部招聘团队 ⇄ 外部猎头与 RPO**（成本、速度、知识沉淀、雇主品牌归属谁的长期争论；embedded recruiter 是近年的折中）；**候选人体验 ⇄ 筛选效率**（漏斗越严体验越差，被拒者也是客户与口碑）；**AI 筛选的效率 ⇄ 合规与偏见**（简历解析、AI 面试评分、自动排序已在大规模使用，同时被监管盯上：纽约市 Local Law 144 要求自动化决策工具做偏见审计并公示、欧盟 AI 法案把招聘划为高风险场景、伊利诺伊州对 AI 视频面试单独立法；业内既离不开它，也在诉讼与审计里学做记录）；**offer 谈判的锚定 ⇄ 薪酬透明**（多地薪酬区间披露立法把谈判起点从『你现在多少』改成『这个岗位值多少』，问薪酬历史在不少法域已被禁止）；**counter-offer 该不该接**（猎头几乎一致反对，认为留下来的人多数一年内还是会走，但这条业内定论的证据基础本身也在被质疑）；**入职后早期流失算谁的**（保证期与退款条款把这场争论直接写进了合同）。(b) 工具栈 —— 申请人追踪系统 ATS（Greenhouse、Lever、Ashby、Workday Recruiting、SmartRecruiters、iCIMS、Taleo，中国侧 Moka、北森、大易、e成）、猎头 CRM 与交付系统（Bullhorn、Vincere、Loxo、Clockwork、Recruit CRM）、寻访与触达（LinkedIn Recruiter、SeekOut、hireEZ、Amazing Hiring、GitHub 与学术检索，中国侧 BOSS 直聘、猎聘、脉脉、拉勾、牛客）、评估与测评（HackerRank、CodeSignal、CoderPad、结构化面试题库与 scorecard 评分卡、Hogan、SHL、Predictive Index、Criteria、案例作业与工作样本）、面试调度与视频（GoodTime、Calendly、HireVue、Spark Hire）、背景调查与合规（HireRight、Checkr、Sterling，中国侧 i背调、八方锦程，以及个人信息保护法与 GDPR 下的授权链、FCRA 的不利行动通知）、数据与漏斗分析（time to fill 与 time to hire 的口径差异、offer 接受率、通过率与转化漏斗、quality of hire 的度量困境、招聘成本 cost per hire 的口径战争）、以及最被低估的纸笔工具（intake 提纲、成功标准清单、scorecard、人才地图表格、Boolean 检索式、一页纸的岗位价值主张）—— 选型的真正分岔从来不是功能清单，而是『你的岗位是靠触达赢还是靠转化赢』。(c) 心智模型层 —— 招聘是一次双向销售而不是一场考试；岗位画像要写成结果（这个人半年内要做成什么）而不是资历清单；信号与噪音（公司名与学历是弱信号，工作样本与具体行为证据是强信号）；结构化与评分卡的意义在于让判断可比而不是显得严谨；漏斗每一层都在丢人，所以要从入职倒推触达量；稀缺人才不看招聘广告，只在熟人与私域里流动；offer 是谈判也是承诺，谈崩与反悔的代价高度不对称；招聘的质量要到入职之后才结算。(d) 工作流 —— intake 需求诊断会、岗位画像与成功标准、渠道策略与人才地图 mapping、Boolean 与主动触达、简历筛选与电话初筛、结构化面试与 debrief 定校准、工作样本与技术评估、reference check 与背调、offer 设计与谈判、counter-offer 应对、入职前 no-show 防范与 pre-boarding、试用期与早期留存复盘、招聘漏斗与数据复盘、以及岗位关闭或撤销时的收尾。(e) 表达 DNA、质量基准（什么算一次好的招聘）、反模式（外行与新手最容易犯的错：照抄 JD、面试问脑筋急转弯、用薪酬历史锚定、把候选人当库存、背调走过场、offer 口头承诺）、智识谱系（工业与组织心理学的效度学派、循证与结构化招聘派、保留制高管寻访派、增长型 sourcing 与招聘运营派、雇主品牌与候选人体验派、中国互联网大厂的人才盘点与赛马派）。) Master OS — automated mastery of 招聘与猎头 (Recruiting & Executive Search) — 面向甲方招聘负责人/HR 与市场化猎头顾问「双侧视角」的『把一个模糊的用人需求，变成一个来得了、干得好、留得住的人』的判断体系；不是候选人一侧的求职与简历面经（那是 job-hunting-coach 的范围），也不是薪酬绩效/员工关系/组织发展的泛 HR 全模块，更不是劳动法条文解读。覆盖：(a) 第一性张力 —— 这行的核心世界观分歧：**需求诊断优先 ⇄ 快速供给优先**（用人经理提来的岗位需求几乎总是一张愿望清单，资深招聘先开 intake 会把『必须有』与『最好有』拆开、把画像逼成可证伪的成功标准；但按成单计酬的猎头把诊断时间压不进单价里，于是行业里同时存在『先诊断再搜寻』和『先扔简历再说』两种作业习惯）；**结构化面试 ⇄ 看人的直觉**（工业与组织心理学近一个世纪的效度元分析一致指向：结构化面试、工作样本、认知能力测验的预测效度明显高于非结构化面谈与经验年限，但一线用人经理绝大多数仍相信自己聊两句就能看准人——这是本行最大的知行落差，也是所有循证招聘流派的出发点；顺带一提，业内长期奉为圭臬的 Schmidt-Hunter 效度排序近年被重新校正，工作样本的效度被下调，这场修正本身就是本行必须如实呈现的争议）；**能力素质 ⇄ 文化匹配**（culture fit 既是最常被写在拒信里的理由，也是被批评得最凶的偏见外壳，Google 一派主张改口叫 culture add，看的是这个人补上了团队缺的东西，而不是像不像我们）；**主动寻访 sourcing ⇄ 被动投递漏斗**（高端与稀缺技能岗只有 outbound 人才地图一条路；量大岗位靠渠道效率、转化率与自动化，两条路的技能树几乎不重叠）；**人才地图是资产 ⇄ 人才地图是浪费**（保留制猎头把 mapping 当交付物的一部分，成功付费猎头认为地图做完单子已经黄了）；**保留制 retained ⇄ 成功付费 contingency**（按阶段预付、独家、深度地图 vs 多家赛马、入职才收钱、速度压倒深度；两种商业模式塑造出两种截然不同的作业节奏、候选人对待方式与职业道德边界，比如 off-limits 不挖回自己安置过的人）；**内部招聘团队 ⇄ 外部猎头与 RPO**（成本、速度、知识沉淀、雇主品牌归属谁的长期争论；embedded recruiter 是近年的折中）；**候选人体验 ⇄ 筛选效率**（漏斗越严体验越差，被拒者也是客户与口碑）；**AI 筛选的效率 ⇄ 合规与偏见**（简历解析、AI 面试评分、自动排序已在大规模使用，同时被监管盯上：纽约市 Local Law 144 要求自动化决策工具做偏见审计并公示、欧盟 AI 法案把招聘划为高风险场景、伊利诺伊州对 AI 视频面试单独立法；业内既离不开它，也在诉讼与审计里学做记录）；**offer 谈判的锚定 ⇄ 薪酬透明**（多地

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。

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

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。

调香师与香水 (调香师 / 香水 (Perfumery & Fragrance) — 香水创作与香气调配的职业认知操作系统，从业者/调香师/评香师/学习者视角。覆盖: (a) 第一性张力 — codifiable 理论层 (原料知识/香料化学/嗅觉家族分类/accord 和弦/配方结构 %/挥发度金字塔/IFRA 法规) ⇄ tacit 校准层 (嗅觉记忆/闻香训练/「the nose」/创作直觉/盲嗅识别)，这行的核心矛盾是「可背诵的原料与公式」与「不可言传的嗅觉记忆与品味」之间，嗅觉记忆是极致 tacit 技能; (b) 法系传统 vs 分子/合成派 — 法国 Grasse 天然香料 + haute parfumerie 艺术传统 (天然精油/原精/学徒制) vs 现代分子派 (aroma chemicals 香基/captives 专利分子/headspace 顶空捕香/功能香精)，两套对「香水是什么」的世界观; (c) 培养/传承 — ISIPCA (凡尔赛香水学校) + 四大香精公司内部调香学校 (Givaudan/Firmenich(DSM-Firmenich)/IFF/Symrise) + 学徒制 + 「鼻子」tacit 校准; 角色分工: perfumer(parfumeur 调香师) vs evaluator(评香师) vs flavorist(食用香精师); (d) 行业结构 — 四大香精公司寡头 (Givaudan/DSM-Firmenich/IFF/Symrise) + Mane/Robertet/Takasago，为品牌做 B2B 命题创作 (the brief → creation → mods 模型); vs niche/indie 小众独立香水 (artisanal/直营); 天然 (Grasse/精油) vs 合成 (香基/captives) 的成本与可持续之争; (e) 创作层 — 香调金字塔 (top/heart/base notes 前中后调)、accord 和弦、配方 (酒精中 % 浓度)、浓度分级 (parfum/EDP/EDT/EDC)、调香师的「香风琴」orgue、trials/mods 试样迭代、weighing 称量精度; (f) 法规与安全 — IFRA standards (原料限用)、EU 致敏原标签 (26→80+ allergens)、REACH、橡苔/atranol 限用、经典香水 (Mitsouko/Chanel No.5) 因法规被迫重配 (reformulation) 与创作自由之张力; (g) 评价/批评 — Luca Turin & Tania Sanchez (《Perfumes: The Guide》《The Secret of Scent》气味的科学)、香评人、Fragrantica/Basenotes 社区、vintage vs reformulation 之争、niche vs designer 之争。学派分歧: 法系天然传统派 vs 分子合成派、天然纯粹派 vs 合成实用派、haute parfumerie/niche 艺术派 vs mass designer 商业派、「鼻子=艺术家」vs「调香师=香气工程师/技师」、嗅觉科学之争 (Luca Turin 振动理论 vs 主流形状/受体理论)。不含: 香薰蜡烛/家居香氛纯生产营销、芳香疗法健康宣称 (aromatherapy)、纯化妆品配方学 (超出香精范畴)、DIY 家用香氛套件、精油传销/MLM。) Master OS — automated mastery of 调香师 / 香水 (Perfumery & Fragrance) — 香水创作与香气调配的职业认知操作系统，从业者/调香师/评香师/学习者视角。覆盖: (a) 第一性张力 — codifiable 理论层 (原料知识/香料化学/嗅觉家族分类/accord 和弦/配方结构 %/挥发度金字塔/IFRA 法规) ⇄ tacit 校准层 (嗅觉记忆/闻香训练/「the nose」/创作直觉/盲嗅识别)，这行的核心矛盾是「可背诵的原料与公式」与「不可言传的嗅觉记忆与品味」之间，嗅觉记忆是极致 tacit 技能; (b) 法系传统 vs 分子/合成派 — 法国 Grasse 天然香料 + haute parfumerie 艺术传统 (天然精油/原精/学徒制) vs 现代分子派 (aroma chemicals 香基/captives 专利分子/headspace 顶空捕香/功能香精)，两套对「香水是什么」的世界观; (c) 培养/传承 — ISIPCA (凡尔赛香水学校) + 四大香精公司内部调香学校 (Givaudan/Firmenich(DSM-Firmenich)/IFF/Symrise) + 学徒制 + 「鼻子」tacit 校准; 角色分工: perfumer(parfumeur 调香师) vs evaluator(评香师) vs flavorist(食用香精师); (d) 行业结构 — 四大香精公司寡头 (Givaudan/DSM-Firmenich/IFF/Symrise) + Mane/Robertet/Takasago，为品牌做 B2B 命题创作 (the brief → creation → mods 模型); vs niche/indie 小众独立香水 (artisanal/直营); 天然 (Grasse/精油) vs 合成 (香基/captives) 的成本与可持续之争; (e) 创作层 — 香调金字塔 (top/heart/base notes 前中后调)、accord 和弦、配方 (酒精中 % 浓度)、浓度分级 (parfum/EDP/EDT/EDC)、调香师的「香风琴」orgue、trials/mods 试样迭代、weighing 称量精度; (f) 法规与安全 — IFRA standards (原料限用)、EU 致敏原标签 (26→80+ allergens)、REACH、橡苔/atranol 限用、经典香水 (Mitsouko/Chanel No.5) 因法规被迫重配 (reformulation) 与创作自由之张力; (g) 评价/批评 — Luca Turin & Tania Sanchez (《Perfumes: The Guide》《The Secret of Scent》气味的科学)、香评人、Fragrantica/Basenotes 社区、vintage vs reformulation 之争、niche vs designer 之争。学派分歧: 法系天然传统派 vs 分子合成派、天然纯粹派 vs 合成实用派、haute parfumerie/niche 艺术派 vs mass designer 商业派、「鼻子=艺术家」vs「调香师=香气工程师/技师」、嗅觉科学之争 (Luca Turin 振动理论 vs 主流形状/受体理论)。不含: 香薰蜡烛/家居香氛纯生产营销、芳香疗法健康宣称 (aromatherapy)、纯化妆品配方学 (超出香精范畴)、DIY 家用香氛套件、精油传销/MLM。: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on 调香师 / 香水 (Perfumery & Fragrance) — 香水创作与香气调配的职业认知操作系统，从业者/调香师/评香师/学习者视角。覆盖: (a) 第一性张力 — codifiable 理论层 (原料知识/香料化学/嗅觉家族分类/accord 和弦/配方结构 %/挥发度金字塔/IFRA 法规) ⇄ tacit 校准层 (嗅觉记忆/闻香训练/「the nose」/创作直觉/盲嗅识别)，这行的核心矛盾是「可背诵的原料与公式」与「不可言传的嗅觉记忆与品味」之间，嗅觉记忆是极致 tacit 技能; (b) 法系传统 vs 分子/合成派 — 法国 Grasse 天然香料 + haute parfumerie 艺术传统 (天然精油/原精/学徒制) vs 现代分子派 (aroma chemicals 香基/captives 专利分子/headspace 顶空捕香/功能香精)，两套对「香水是什么」的世界观; (c) 培养/传承 — ISIPCA (凡尔赛香水学校) + 四大香精公司内部调香学校 (Givaudan/Firmenich(DSM-Firmenich)/IFF/Symrise) + 学徒制 + 「鼻子」tacit 校准; 角色分工: perfumer(parfumeur 调香师) vs evaluator(评香师) vs flavorist(食用香精师); (d) 行业结构 — 四大香精公司寡头 (Givaudan/DSM-Firmenich/IFF/Symrise) + Mane/Robertet/Takasago，为品牌做 B2B 命题创作 (the brief → creation → mods 模型); vs niche/indie 小众独立香水 (artisanal/直营); 天然 (Grasse/精油) vs 合成 (香基/captives) 的成本与可持续之争; (e) 创作层 — 香调金字塔 (top/heart/base notes 前中后调)、ac

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。

Assign items to a CLOSED label vocabulary that is too large to put in a prompt — product taxonomies, category hierarchies, tag vocabularies, routing tables, ICD/SIC-style code lists. A cheap model writes the label it thinks the vocabulary would use, and an embedder snaps that writing onto the nearest legal value, so the schema is never transmitted and the output is always in-vocabulary. Use for "classify these into our taxonomy", "tag these against the existing tag list", "map these queries to categories", "the enum is too big to send", or a Literal/enum that hits a provider cap. NOT for a vocabulary that fits in a prompt — structured output measured 0.701 acc@1 there against this pattern's 0.564. NOT for open-ended labelling with no fixed vocabulary, and not for ranked retrieval over documents (bm25).

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。

Exports a Claude.ai workspace — its custom instructions and its uploaded knowledge files — into a bundle that can be re-imported elsewhere. Use for "back up my project instructions", "export my project knowledge", "copy this workspace to a new one", "migrate my project to another account", or "recreate this setup somewhere else". Operates on the Claude.ai workspace you are talking in, and reads nothing from disk.

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。

Counts and compares blog posts across a target and competitors, audits content freshness via sitemap lastmod dates, and maps competitor organic keywords (US, non-branded, informational) against the target to surface ranking gaps. Use when asked to compare blog counts, content volume, publishing cadence, content freshness, keyword mapping, keyword gap analysis, or competitor keyword reports — e.g. "how many blog posts does X have vs Y", "how fresh is content on X", "where does [target] rank for [competitor] keywords", "keyword gap between X and Y". Works from company names alone. Always use for blog comparison, freshness audits, and keyword mapping tasks.

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。

Audits any developer documentation site across 33 checks in 7 categories and produces a scored report (out of 100) with Pass / Warn / Fail status per check. Use this skill whenever a user provides a docs URL and asks to audit it, review it, score it, check its quality, or evaluate it for AI discoverability, SEO, structure, content, or completeness. Also trigger when the user says "run a docs audit", "audit these docs", "check this documentation", "how good are the docs for X", or pastes a docs URL with any evaluative intent. Always use this skill — do not attempt a freeform docs review without following this structured workflow.

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。

Computes a numeric or categorical answer to a quantitative data-science question by cleaning and analyzing local data files (CSV, Excel, TSV, and scientific formats .npz/.fits/.h5) with pandas, numpy, and scipy. Use whenever a task ships its own dataset (in whatever local directory it provides) and asks you to derive a value via statistical, geospatial, temporal, ratio, percentage, growth-rate, correlation, signal-processing, orbital, or forecasting analysis. Spans domains including archeology (demographics, paleoclimate proxies, radiocarbon dating, historical conflicts); biomedical/bioinformatics (tumor histology, genes, proteins, peptides, genomic variants); environmental (water quality, bacterial/Enterococcus exceedance, rainfall correlations, environmental justice); legal/consumer (fraud, identity theft, consumer complaints by state/metro); wildfire (incidents, causes, suppression costs, acres burned, fatalities, geospatial intersections); and astronomy/heliophysics/space weather (satellite telemetry TLE/Swarm/SP3, indices OMNI/GOES, solar activity, atmospheric density, orbital mechanics, forecasting).

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。

Operate ArvanCloud (arvancloud.ir) through its REST APIs, including CDN and DNS records, domains, cache purge, WAF and rate limits, Cloud Server (IaaS v3, v1 and the undocumented v2 backups), Object Storage, Edge Computing, Cloud Container, VOD, Live and Video Ads, plus Let's Encrypt DNS-01 certificates via acme.sh dns_arvan. Use when the user wants to list, create, change or delete anything on ArvanCloud, take an account inventory, find out which account a key belongs to, check quota or usage, or debug an ArvanCloud API error. Also trigger on hosts like napi.arvancloud.ir, ecc.{region}.arvanapis.ir, storage.arvanapis.ir, dejban.arvancloud.ir, an "Apikey" Authorization header, the dns_arvan plugin, or one of the user's ArvanCloud-hosted domains.

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。

Review UI usability using Steve Krug's principles and produce a scannable report. Use for UX audits of screenshots, URLs, or code. Don't use for brand critique, WCAG audits, or backend/API review.

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。

Suede-owned conversion-path discipline for pages. Turns a page into a conversion path: hero, friction, proof, CTA, pricing, A/B ideas, quick wins, and mobile CRO. Use when a live or drafted page needs conversion-rate work on its structure and persuasion path. NOT FOR: a scored SEO/AI-visibility audit (use suede-seo-audit); a fast launch-appeal grade (use suede-visibility-grader); writing the copy itself (use suede-copy).

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。

Suede Labs skill that turns messy creator materials into a local, offline rights-and-provenance transfer package: inventoried and hashed assets, a normalized suede-intake.json manifest, credits and splits, license notes, provenance, and a missing-information report, validated by a bundled stdlib script. Use when a creator needs to hand a song, release, or project to a collaborator, advisor, registry, marketplace, or label; when someone asks for a rights package, intake package, or handoff folder; or when a validated manifest is needed before licensing or royalty-routing review. Carries questions, not answers: building the package clears nothing and uploads nothing. NOT FOR: finding or investigating the rights gaps in the first place (use suede-rights-audit); linting a release folder's files and metadata (use suede-release-linter); a sync one-sheet (use suede-sync-packaging).

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。

Suede Labs Google Play delivery skill: ship an Android release end to end from the agent interface, without opening the Play Console. Set up credentials, upload an AAB, promote between tracks, stage or complete a rollout, push per-locale release notes, and prove against the Play Developer API what is actually live. One step stays a Console action by design and the skill hands it to you: granting the service account release access the first time. Use when uploading or promoting an Android build, wiring a Play service account and fastlane supply lanes, fixing per-versionCode changelogs, raising or halting a staged rollout, or answering what version and fraction production is really serving. NOT FOR: planning or building the app itself (use android-app-factory); live listing and keyword audits (use suede-aso); CI required checks (use suede-ci-gate); iOS release (a private Suede Labs companion, not in this pack: ios-app-store-release).

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。

Suede AI umbrella router for the public Suede pack: selects the right specialist across copy, design, code review and grading, SEO and visibility, launch packaging, MCP QA, iOS and Android shipping, growth, and creator rights work. Use when a request crosses two or more Suede lanes, when the user wants the full public skill pack loaded from one installable path, when they ask which Suede skill fits a task, or when only this umbrella skill is installed. NOT FOR: a request that names one lane and can go straight to its specialist; a multi-file repo change that should be built and reviewed as one DAG (use suede-graph-flo-xr).

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。

Suede AI CI and branch-protection wiring for any repo and any stack: path-aware jobs, a single aggregator required check that cannot deadlock, lockfile hygiene, runtime pinning from the repo, and the exact branch-protection settings. Use when asked to set up CI, protect main, make CI block a bad merge, fix a required check that hangs pending forever, or repair duplicate or misfiring pipelines. Detects the repo's real apps, package managers, and runtime versions first; emits workflow files and settings, never pushes or flips protection itself. NOT FOR: reviewing or grading the change the gate is failing on (use suede-code); designing the AI eval cases to wire in (use suede-ai-eval); branch and worktree hygiene (a private Suede Labs companion, not in this pack).

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。

Suede AI MCP release QA, scoped to this pack's own server (mcp/suede-skills-mcp.mjs) and its catalog, install, and docs surface. Runs the full JSON-RPC lifecycle against a live server (initialize, notifications/initialized, ping, tools/list, tools/call, resources/list, resources/read, prompts/list, prompts/get), plus protocol negotiation, closed input and output schemas, tool annotations, structuredContent with text fallbacks, malformed-input probes, clean stdio, catalog-to-folder agreement, and install-path language. Use when the MCP server, mcp/catalog.json, a tool, resource, or prompt definition, or the MCP install docs change, or before publishing an MCP release. A check that did not run against the live server is a FAIL, not a skip. NOT FOR: a generic third-party MCP server, which this skill's hardcoded surface does not describe; fixing or testing the public install path itself (use suede-launch-packaging).

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。

Suede-owned editorial pipeline for agent-run content: six roles with written contracts, one inspectable record that travels between them, and a distribution stage that gives every asset its own argument instead of a shorter draft. Use when content agents return generic, duplicated, or unsourced work, when one flagship piece has to carry a week of distribution, when someone asks to build an AI content team or one-person media company, or when a founder wants a weekly interview-led content system across personal and company accounts. NOT FOR: choosing which topics, pillars, or clusters to cover (use suede-content-strategy); platform mix, cadence, calendars, or listening (use suede-social); an Instagram-specific program (use suede-instagram-growth); running a stage on a schedule with state and stop conditions (use suede-marketing-loops); lane ownership for agents changing code (use suede-agent-teams); writing the flagship piece itself (use suede-ship-copy).

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Make an original animated music video (MV / PV) for a song from its audio file plus lyrics, in the Vocaloid / J-pop lyric-video tradition: 手書き/tegaki (V家手书, 手描きMV, ボカロPV), 文字PV and kinetic typography (リリックモーション, リリックビデオ, 歌詞動画, 歌词视频, 动态歌词), anime-illustration MVs with an original character — for any mood, from dark ballads to bright upbeat summer pop. Renders to MP4 with a deterministic Canvas2D/WebGL2 engine in a headless browser: JIZURA lyric motion, AI-generated art, optional Blender toon 3D, beat-locked editing, 9:16 vertical/Shorts version. Use it whenever the user wants a music video, MV, PV, lyric video or beat-synced animation for a song, e.g. "make an MV for my song", "turn this track into a lyric video", "给这首歌做个MV/PV", "做个V家手书", "この曲のMVを作って", "ボカロPV作って", "縦型ショートも" — even if they only give a .wav/.mp3 and say "make a cool video for it". Not for editing existing footage or clip compilations.

npm package maintenance and lifecycle management for monorepo extensions. Covers health audits, dependency sync, version bumping, changelog updates, pre-publish checks, coordinated publishing, and post-publish verification. **Triggers — use this skill when:** - User asks to "publish", "release", or "version bump" extensions/packages - User says "audit packages", "check package health", "dependency sync" - User asks to "update changelogs", "prepare release", "pre-publish check" - User mentions "npm publish", "version management", "package lifecycle" - User wants to "sync dependencies" or "align versions" across packages - User asks "what needs publishing" or "which packages changed" **Covers:** Monorepo with multiple npm packages under `extensions/`. Each package has its own package.json, CHANGELOG.md, README.md, and version. Packages are scoped (e.g. `@e9n/pi-*`) and published individually.

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Parse git history and produce or update a CHANGELOG.md following the Keep a Changelog convention. Supports Conventional Commits, basic prefix conventions, and unstructured commit messages. Intelligently categorizes changes, detects breaking changes, links to PRs/issues, and handles both initial generation and incremental updates. **Triggers — use this skill when:** - User asks to "generate", "create", "update", or "write" a changelog - User mentions "CHANGELOG", "changelog", "release notes" - User says "document changes", "what changed since last release" - User wants to "prepare a release" and needs a changelog entry - User asks to "clean up" or "reformat" an existing changelog **Covers:** Any git-based project. Handles Conventional Commits (feat/fix/chore), Angular convention, basic prefixes (Add/Fix/Remove), and freeform commit messages. Outputs Keep a Changelog format with optional Common Changelog enhancements.

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Generate comprehensive status reports for git repositories. Analyzes commits, codebase structure, type errors, branch health, dependency status, GitHub PRs/issues/CI, working tree changes, and optionally integrates with `td` (task management CLI) if a `.todos` folder is present. **TRIGGERS - Use this skill when:** - User asks for the status of a git project or repo - User asks "what's going on in [project]" or "give me an overview of [repo]" - User wants a project summary, progress report, or codebase overview - User asks about recent commits, code structure, or project health - User says "check my project" or "project status" **Output:** A rich, structured text report covering overview, branches, commit history, codebase breakdown, GitHub activity, dependency health, issues/errors, working tree changes, task management, and summary.

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Comprehensive clinical laboratory data harmonization for multi-source healthcare analytics. Convert between US conventional and SI units, standardize numeric formats, and clean data quality issues. This skill should be used when you need to harmonize lab values from different sources, convert units for clinical analysis, fix formatting inconsistencies (scientific notation, decimal separators, whitespace), or prepare lab panels for research.

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Use when a Godot project uses or considers C# (.NET) or native code - when C# is the right call and its export limits (no web export), C# node patterns with generated SignalName/StringName caching, plain C# rule libraries tested with dotnet test, and GDExtension (godot-cpp, godot-rust) pinning and build hygiene.

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Plan, art-direct, generate, edit, and quality-check tactile minimal-zine bitmap imagery from almost any subject: landscapes, portraits, objects, products, architecture, interiors, existing photographs, moods, article ideas, cultural essays, data, reviews, and social-media card series. Use for 小红书图片, Instagram carousels, poetic posters, editorial covers, photo restyling, visual essays, evidence-aware explainers, or any request for aged paper, photocopy, risograph, letterpress, sparse type, and restrained single-ink character. Routes the subject before choosing composition, preserves identity and factual content when editing, saves reproducible prompts, invokes the runtime-native image generator, and audits the real raster output. Do not use for glossy commercial ads, deterministic UI/vector assets, or exact diagram rendering.

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。