「uat」の検索結果

Create, edit, evaluate, and package agent skills. Use when building a new skill from scratch, improving an existing skill, fixing a skill that never triggers or fires unreliably, running evals to test a skill, benchmarking skill performance, optimizing a skill's description, reviewing third-party skills for quality, or packaging skills for distribution — even if the user doesn't explicitly say "skill" (e.g. "teach Claude to do X", "make the agent always follow Y"). Not for using skills or general coding tasks.

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This skill should be used when the user asks to "analyze session", "evaluate skill execution", "check session logs", provides a session ID with a skill path, or wants to verify that a skill executed correctly in a past session. Post-hoc analysis of Claude Code sessions to validate skill/agent/hook behavior against SKILL.md specifications.

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Apply when refactoring, evaluating diff size, or tempted to add abstractions, layers, or signal threading. Bias toward deletion and the smallest change that solves the problem.

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Build or resume mathematical-modeling competition work, including CUMCM, MCM/ICM, graduate and regional contests, data challenges, and open-topic statistical modeling. Guide problem framing, modeling, computation, validation, Chinese or English LaTeX writing, and reviewed PDF/source delivery using current official requirements. Not for ordinary paper polishing.

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Conversion Rate Optimization auditing for landing pages, signup flows, checkout funnels, forms, and CTAs. Identifies friction points, runs heuristic evaluations, produces prioritized recommendations using ICE/PIE frameworks. Use when the user asks about conversion optimization, funnel analysis, landing page audits, form optimization, CTA testing, or checkout improvement.

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Google and Meta paid media account structure evaluation. Audits campaign/ad set architecture against conversion volume minimums, budget thresholds, and targeting overlap. Identifies over-segmentation, under-segmentation, budget fragmentation, and structural anti-patterns blocking algorithmic learning. Provides consolidation roadmaps with migration plans. Use when inheriting accounts, quarterly health checks, or before scaling budgets.

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Create mathematical animations with Manim Community Edition(manimce), with optional TTS voiceover and synced subtitles. Generates distinctive, production-grade animations that avoid generic "AI slop" aesthetics. Use when user wants to animate concepts, equations, illustrate proofs, visualize algorithms, create math explainers, or produce 3Blue1Brown-style videos.

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Expert guidance for DeepEval, the open-source framework for unit testing LLM applications. Helps developers write test cases, define custom metrics, and integrate LLM quality checks into CI/CD pipelines using a pytest-like interface.

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Analyze contracts for risks, check completeness, and provide actionable recommendations. Use when a user asks to review a contract, check an agreement for red flags, analyze contract terms, find risky clauses, review an NDA, evaluate a service agreement, or audit employment contract terms. Supports employment contracts, NDAs, service agreements, and vendor contracts.

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Understand essential business finance — profit margins, unit economics, cash flow, LTV/CAC, and the 4 methods to increase revenue. Use when: analyzing business profitability, making pricing decisions, evaluating SaaS unit economics, financial planning.

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Screen job applications against requirements and score candidates objectively. Use when a user asks to review applications, evaluate candidates, screen resumes, rank applicants, assess qualifications against a job description, shortlist candidates, or build a hiring scorecard.

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A great product that nobody knows about is a failed product. Go-to-market strategy is how you get your product into customers' hands. Not marketing in the abstract - specific motions, channels, and sequences for your specific situation. This skill covers GTM motion selection (product-led, sales-led, community), channel strategy, launch sequencing, early customer acquisition, and the critical transitions between GTM phases. Use when "go to market, GTM, launch strategy, how to get customers, sales vs product-led, channel strategy, market entry, customer acquisition, distribution strategy, product launch, getting first customers, sales motion, bottoms up, top down sales, go-to-market, gtm, launch, product-led-growth, sales, channels, customer-acquisition, distribution, marketing" mentioned.

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Review code architecture for maintainability, catch structural issues before they become debtUse when "Reviewing pull requests with structural changes, Planning refactoring work, Evaluating new feature architecture, Assessing technical debt, Before major releases, When code feels "hard to change", architecture, code-review, refactoring, design-patterns, technical-debt, dependencies, maintainability" mentioned.

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Expert in creating endings that demand continuation. Covers serialized content, episode structure, tension building, and the psychology of incomplete narratives. Knows how to create anticipation without frustration. Use when "cliffhanger, to be continued, serialized, episode ending, keep them coming back, next episode, part 2, " 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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Flagship intra-paper self-consistency forensics: does the paper contradict ITSELF across abstract/intro/tables/body/appendix, and does the method DESCRIBED match the method EVALUATED? Needs no external ground truth — works PDF-only (L0). Runs a deterministic arithmetic pass + a fresh cross-model semantic pass, every finding span-anchored to the evidence ledger (claims.json), reviewer≠adjudicator. Emits consistency-audit.findings.json; NEVER computes the verdict. Triggers: "consistency audit", "check the paper against itself", "self-consistency", "内部自洽".

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Build the deterministic evidence ledger (artifact_manifest.json + claims.json) that every other Anti-Autoresearch auditor reads. One pass inventories artifacts, derives the observability level (L0 PDF-only / L1 +LaTeX / L2 +repo+results) by fixed rule, and extracts span-anchored, hashed, checkable claims (numbers, comparisons, scope, method, baselines, citations, captions, table cells) into claims.json. An OPTIONAL additive cross-model pass ADDS span-anchored semantic claims — method, theorem statements with their assumptions, definitions, proof/derivation steps and equations, scope, baselines, conclusions, the motivation span, and reproducibility-artifact references (the proof, derivation, and structure anchors the family B/D/G auditors need) — it never invents a number, emits a finding, or computes a verdict. Run FIRST, before any audit skill. Triggers: "build the ledger", "extract claims", "prep for integrity audit", "evidence ledger", "建证据账本".

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。

Audit experiment integrity against the evidence ledger. At L2 (repo + result files present) a fresh cross-model reviewer reads the eval code line-by-line for fake/derived ground truth, score self-normalization, phantom results (a paper number with no backing file/key), dead/uncalled metric code, verified-scope inflation, method-described ≠ method-evaluated drift, synthesized-looking results, placeholder/fake data still wired into a released result, code-output ≠ reported-number mismatch, and missing reproducibility artifacts (an empirical/agent/LLM paper shipping neither code nor the prompts/configs its results need) — every finding span-anchored to a ledger claim_id. At L0/L1 (PDF / source only) the same patterns are surfaced as info-level 'could-not-verify' signals where the ledger gives an anchor (observability_level_required:2) — NEVER a fraud verdict from a PDF. The reviewer PROPOSES findings; tools/adjudicate_findings.py computes the verdict. Detect-only. Triggers: "experiment forensics", "audit the results", "check the eval code", "实验诚实度".

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。

Architecture Decision Framework workflow skill. Use this skill when the user needs Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system design and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

antigravity-skill-orchestrator workflow skill. Use this skill when the user needs A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

antigravity-skill-orchestrator workflow skill. Use this skill when the user needs A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Pieter Levels (@levelsio) 视角. 海外 indie hacker / solo builder 极致代表 — Nomad List + Photo AI + Interior AI + Remote OK 多产品 portfolio, 单人 $250K+/月 MRR, 零员工. 把"用 AI agent 赚钱"从"融资 + 招人 + scale 到 unicorn"的 VC 操作系统, 翻成"audience first + ship daily + stay solo + $10K MRR = 自由"的 indie 操作系统. 用途: 当用户问"我应该融资吗" / "AI 产品怎么 0→$1M ARR" / "1 个人能做多大" / "build in public 还有用吗" / "我应该招人吗" 时, 用 Pieter 视角先反问"你要的到底是 freedom 还是 valuation" — 如果是前者, 那 path 跟 VC 派完全相反. 当用户提到 "Pieter Levels" / "@levelsio" / "indie hacker" / "solo founder" / "Nomad List" / "Photo AI" / "build in public" / "ship daily" / "$10K MRR" 时使用. 即使用户只是说 "我想做个 SaaS 副业" / "怎么 bootstrap" 也应触发.

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产品设计 / UX 设计 (产品设计 / UX 设计 (Product Design / UX Design) — 数字产品的用户体验设计：从用户研究 → 信息架构 → 交互设计 → 视觉/UI → 可用性测试 → 设计系统的认知操作系统，面向 UX designer / product designer / interaction designer / UX researcher / design systems engineer / design lead，以及想入行、转岗、服务这行(设计外包、设计工具厂商、研究平台)的视角。覆盖: (a) 第一性张力 — **用户中心/研究驱动 (user-centered, 'you are not the user', research before pixels, observe behavior not opinions) ⇄ 商业目标/约束/交付 (business goals, north-star metrics, ship it, designer 服务于产品成功不是个人作品集)**; **设计直觉/品味/craft (taste, aesthetics, 'attractive things work better' — Norman 情感化设计) ⇄ 数据/实验/A-B 测试 (data-driven, metrics, experimentation, 'opinions are not data')**; **用户说的 (stated preference, 访谈里说喜欢) ⇄ 用户做的 (revealed behavior, 行为观察 > 自陈, usability test 看人真实卡在哪)**; **一致性/设计系统/规范 (consistency, design system, Jakob's law 用户带着别处的习惯来, 复用组件) ⇄ 创新/打破模式 (innovation, 该不该破规范)**; **减法/简化 (simplicity, Krug 'Don't Make Me Think', less but better — Dieter Rams) ⇄ 功能丰富/利益相关者塞需求 (feature creep, stakeholder pressure)**; **UX(体验/流程/研究) ⇄ UI(视觉/像素/组件)** 的职责之争, **designer 该不该写代码 (design engineer / 'should designers code')**; (b) 核心工作流 / pipeline (最标准、最易蒸高质量+CLI 化) — Double Diamond (发现 discover → 定义 define → 开发 develop → 交付 deliver) / Design Thinking (共情 empathize → 定义 → 构思 ideate → 原型 prototype → 测试 test) / Design Sprint (Jake Knapp 5 天冲刺); 完整链: 用户研究 (访谈/问卷/可用性测试/卡片分类) → persona / journey map / JTBD → 信息架构 IA + 用户流 user flow → 线框 wireframe (低保真) → 交互/原型 prototype (高保真) → 视觉 UI / 设计系统落地 → 可用性测试 usability testing → handoff 给开发 → 度量迭代 (北极星 / HEART 框架); (c) 工具栈 — 设计/原型 (Figma 绝对主导 / Sketch 衰退 / Adobe XD 已停更 / Framer 高保真+建站 / Penpot 开源 / Principle / ProtoPie 微交互); 协作白板 (FigJam / Miro / Mural); 用户研究 (Maze / UserTesting / Lookback / Dovetail 研究库 / Optimal Workshop 卡片分类树测试 / Hotjar / Microsoft Clarity 热图); 设计系统/交付 (Storybook / 蓝湖(中) / Zeplin / design tokens / Tokens Studio); 度量 (Amplitude / Mixpanel / 北极星指标); AI 新兴 (Figma AI / v0 by Vercel / Galileo AI / Uizard / Cursor 给 design engineer); (d) 知识正典 — Don Norman《The Design of Everyday Things》(affordance/signifier/mapping 圣经)、Steve Krug《Don't Make Me Think》(可用性入门)、Alan Cooper《About Face》《The Inmates Are Running the Asylum》(交互设计/persona 起源)、Jakob Nielsen 10 Usability Heuristics + NN/g 文章库、Jake Knapp《Sprint》、Jeff Gothelf《Lean UX》、Teresa Torres《Continuous Discovery Habits》、Erika Hall《Just Enough Research》、Julie Zhuo《The Making of a Manager》、《Refactoring UI》(Adam Wathan/Steve Schoger)、《Universal Principles of Design》、Laws of UX (Jon Yablonski)、《100 Things Every Designer Needs to Know About People》(Susan Weinschenk)、IDEO/Stanford d.school 设计思维材料; (e) figures/流派 — 认知心理/人因派 (Don Norman 认知科学奠基、Susan Weinschenk 行为心理、Kathryn Whitenton); 可用性工程派 (Jakob Nielsen 启发式/折扣可用性、Steve Krug、Jared Spool UIE); 交互设计/目标导向派 (Alan Cooper goal-directed/persona、Kim Goodwin); 设计思维派 (IDEO Tim Brown、David Kelley d.school); 精益/持续探索派 (Jeff Gothelf Lean UX、Teresa Torres continuous discovery、Marty Cagan《Inspired》产品发现); 设计系统/系统化派 (Brad Frost Atomic Design、Nathan Curtis design tokens、Alla Kholmatova); 视觉/UI craft 派 (Adam Wathan & Steve Schoger Refactoring UI、Dieter Rams 'less but better' 工业设计遗产); 设计领导/职业派 (Julie Zhuo、Aarron Walter 情感化设计、John Maeda); 移动优先 (Luke Wroblewski 'Mobile First'); (f) 行业话术/黑话 — affordance 可供性 / signifier 意符 / mental model 心智模型 / IA 信息架构 / heuristic evaluation 启发式评估 / usability 可用性 / a11y accessibility 无障碍 / WCAG / persona 用户画像 / journey map 用户旅程 / JTBD jobs-to-be-done / north-star metric 北极星 / HEART 框架 / wireframe 线框 / mockup / prototype 原型 / fidelity 保真度 (lo-fi/hi-fi) / design system 设计系统 / design token 设计令牌 / atomic design 原子设计 / component library 组件库 / handoff 交付 / red routes 关键路径 / dark pattern 暗黑模式 / Fitts's law / Hick's law / Jakob's law / Miller 7±2 / progressive disclosure 渐进披露 / above the fold / hamburger menu / skeuomorphism vs flat / micro-interaction / empty state / edge case / happy path / design debt 设计债 / dogfooding / dot voting / affinity mapping 亲和图 / card sorting 卡片分类 / tree testing / A/B test / NPS / SUS (System Usability Scale); (

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。

B2B 大客户销售 (B2B 大客户销售 / 企业级复杂销售 (Enterprise B2B Sales / Complex Selling) — 面向企业客户的高价值、长周期、多干系人复杂销售的职业认知操作系统，从业者(AE/客户经理/SE 售前/销售负责人 VP Sales/CRO)、想入行者、以及服务这行(销售咨询/enablement/RevOps)的视角。覆盖: (a) 第一性张力 — 三大方法论流派之争: **买方主导的诊断式提问 (consultative/discovery-led: SPIN 提问 → 痛点 → 方案, 「像医生先诊断再开方」) ⇄ 卖方主导的教学式挑战 (Challenger: Teach-Tailor-Take control, 用商业洞见 reframe 客户认知, 「像老师挑战客户的既有想法」) ⇄ 资格审查纪律 (MEDDIC/MEDDPICC: 先严格 qualify/disqualify, 「no deal 好过 bad deal」)**; 三派不是非此即彼, 资深人混用, 但底层世界观分歧真实(问 vs 教 vs 筛); 更深层张力 — 「过程/方法论纪律 (process rigor: 预测准确、deal inspection、qualify) ⇄ 关系/信任 (relationship: champion 培养、高管关系、人情)」, 「卖结果/业务价值 (business outcome/ROI、卖给经济决策人) ⇄ 卖产品/功能 (feature selling)」, 「多线程触达买方委员会 (multithreading buying committee) ⇄ 单一 champion 依赖」; (b) 方法论正典 (最标准化、最易蒸出高质量+CLI 化) — MEDDIC/MEDDPICC (Metrics 量化指标/Economic buyer 经济决策人/Decision Criteria 决策标准/Decision Process 决策流程/Identify Pain 痛点/Champion 内部拥护者 + Paper process 签约流程/Competition 竞争), SPIN (Situation/Problem/Implication/Need-payoff 提问序列), Challenger (商业洞见 commercial insight + reframe + 建设性张力 constructive tension + Mobilizer 调动者), Solution Selling (痛点链 pain chain/愿景创建/buying vision), Sandler (前置合约 up-front contract/痛苦漏斗 pain funnel/潜艇七步), Command of the Message (Force Management: 业务价值框架/before-after/decision criteria), Gap Selling (Keenan: 现状 current state → 期望 future state → 差距 the gap/问题中心), Miller Heiman Strategic Selling (蓝表 blue sheet/buying influences: 经济/用户/技术买家 + coach), Value Selling, BANT (老式资格框架, 多被 MEDDIC 取代); (c) 行业结构与角色 — SDR/BDR (开发/约见) → AE/客户经理 (成交) → SE/售前/Solutions Engineer (技术验证/POC/demo) → CSM (客户成功/续约扩张) → Sales Manager/VP Sales/CRO; RevOps (收入运营), Sales Enablement (赋能); land and expand (先落地再扩张)、量化指标 quota/OTE(目标总收入)/配额达成率/pipeline coverage(管道覆盖率 ~3x 业内经验法则)/win rate(赢率)/sales velocity(销售速度)/ramp time(爬坡期)/ACV·ARR·NRR(年合同额/年经常性收入/净收入留存); (d) 销售周期 (the deal/opportunity lifecycle) — prospecting 开发 → discovery 需求挖掘 → qualification 资格审查(MEDDIC) → demo/technical validation/POC 技术验证 → business case/value 业务价值与 ROI → proposal 提案 → negotiation 谈判(procurement 采购/法务/security review) → close 成交 → onboarding/expansion 交付与扩张; 干系人: champion 拥护者 vs coach 线人 vs economic buyer 经济决策人 vs blocker 阻碍者; mutual action plan/close plan(双向行动计划/成交计划); (e) 产出物与节奏 — discovery call(需求电话)、demo、business case、proposal/SOW、MAP(mutual action plan)、forecast(预测: commit/best case/pipeline 类别)、pipeline review/deal review/QBR(季度业务回顾)/account plan(客户计划); (f) 职业/招聘/薪酬 — quota/OTE/comp plan(底薪+提成)/accelerator(加速器)/SPIFF/clawback、ramp、President's Club(顶尖销售俱乐部)、SDR→AE→管理 晋升路径、rep turnover(销售流失率高); (g) 争议/批判 — Challenger 是否过誉(CEB 原始数据被质疑、insight selling 批评)、MEDDIC 沦为填表剧场(box-checking theater, 填字段不真 qualify)、活动指标 vs 质量(spray-and-pray 群发/冷电话存废之争)、AI SDR/自动化淹没收件箱(2024-2025 AI BDR 泡沫 + 邮件送达率崩溃 backlash)、SDR 军团模式是否将死(Winning by Design/signal-based GTM 取代)、配额虚高与销售 burnout、季末打折促单、销售方法论的「宗教化」与培训-认证产业链、最大竞争对手其实是「no decision/维持现状」而非对手; (h) 流派/思想谱系 — 提问诊断派(Rackham SPIN/Bosworth&Eades Solution Selling/Keenan Gap Selling) vs 挑战教学派(Dixon&Adamson Challenger/Force Management Command of the Message) vs 资格纪律派(MEDDIC: Napoli&Dunkel 起源/John McMahon/MEDDICC Andy Whyte) vs 关系战略派(Miller Heiman Strategic/Large Account) vs SaaS 现代收入架构派(Aaron Ross Predictable Revenue/Mark Roberge Sales Acceleration Formula/Jacco van der Kooij Winning by Design bowtie/David Skok 指标) vs 开发-心态派(Jeb Blount Fanatical Prospecting/Sales EQ、Anthony Iannarino、Josh Braun) vs 谈判(Chris Voss Never Split the Difference 战术同理心)。不含: B2C/零售/电商导购销售、纯电话客服/客户支持、纯渠道/分销管理(channel 虽相关但聚焦直销复杂销售)、纯 marketing/需求生成(demand gen 虽上游但本 skill 聚焦销售执行)、纯 CSM 客户成功(虽相关但聚焦 new logo + expansion 的销售动作)。) Master OS — automated mastery of B2B 大客户销售 / 企业级复杂销售 (Enterprise B2B Sales / Complex Selling) — 面向企业客户的高价值、长周期、多干系人复杂销售的职业认知操作系统，从业者(AE/客户经理/SE 售前/销售负责人 VP Sales/CRO)、想入行者、以及服务这行(销售咨询/enablement/RevOps)的视角。覆盖: (a) 第一性张力 — 三大方法论流派之争: **买方主导的诊断式提问 (consultative/discovery-led: SPIN 提问 → 痛点 → 方案, 「像医生先诊断再开方」) ⇄ 卖方主导的教学式挑战 (Challenger: Teach-Tailor-Take control, 用商业洞见 reframe 客户认知, 「像老师挑战客户的既有想法」) ⇄

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。