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概要と使いどころ
AI Engineering Toolkit workflow skill. Use this skill when the user needs 6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching 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。
AI Pricing Skill workflow skill. Use this skill when the user needs When the user wants to price an AI product, choose a charge metric, design pricing tiers, or optimize margins. Also use when the user mentions 'AI pricing,' 'usage-based pricing,' 'consumption pricing,' 'outcome pricing,' 'BYOK,' 'bring your own key,' 'per-seat pricing,' 'pricing tiers,' 'AI margins,' 'cost per token,' or 'pricing model.' This skill covers pricing strategy, packaging, and margin management for AI-native products. Do NOT use for technical implementation, code review, or software architecture 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。
Agent Tool Builder workflow skill. Use this skill when the user needs Tools are how AI agents interact with the world. A well-designed 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。
AI Cold Outreach workflow skill. Use this skill when the user needs When the user wants to build an AI-powered outreach system, write cold emails, improve deliverability, or scale personalized outreach. Also use when the user mentions 'cold email,' 'cold outreach,' 'outreach automation,' 'Instantly,' 'Smartlead,' 'Clay,' 'email sequences,' 'deliverability,' 'personalization at scale,' 'reply rate,' or 'outreach stack.' This skill covers the complete AI cold outreach system from signal detection through conversion. Do NOT use for technical implementation, code review, or software architecture 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。
Accessibility Audit and Testing workflow skill. Use this skill when the user needs You are an accessibility expert specializing in WCAG compliance, inclusive design, and assistive technology compatibility. Conduct audits, identify barriers, and provide remediation guidance 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。
Agent Manager Skill workflow skill. Use this skill when the user needs Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling 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。
Agent Manager Skill workflow skill. Use this skill when the user needs Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling 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。
Accessibility Audit and Testing workflow skill. Use this skill when the user needs You are an accessibility expert specializing in WCAG compliance, inclusive design, and assistive technology compatibility. Conduct audits, identify barriers, and provide remediation guidance 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。
投行并购 (投行并购 / 交易撮合 (Investment Banking M&A / Dealmaking) — 面向并购顾问、企业融资、卖方/买方交易执行的职业认知操作系统，从业者(分析师 Analyst / 经理 Associate / 副总裁 VP / 董事 Director / 董事总经理 MD / 内部公司发展 Corp Dev / PE 投资人)、想入行者、以及服务这行(法律/会计/估值/咨询)的视角。覆盖: (a) 第一性张力 — 投行 M&A 的核心世界观分歧: **价格 vs 价值 (price 是市场愿意付的, value 是内在的, deal 在两者缝隙里成交) ⇄ 确定性 vs 最高价 (certainty of close 对卖方常胜过纸面最高报价) ⇄ 顾问/中介 vs 委托代理 (banker 是 agent, 客户利益 vs 成交费的激励冲突真实存在, 「banker 总想成交」是行业原罪批判)**; 更深层 — 「过程/竞价纪律 (controlled auction 制造竞争张力、信息不对称管理) ⇄ 关系/信任 (relationship banking、长期 coverage、reputational capital)」, 「叙事/包装 (the story, equity story, positioning) ⇄ 数字/尽调 (the numbers, diligence, quality of earnings)」, 「估值的科学外衣 (DCF/comps 的伪精确) ⇄ 谈判的真实定价 (价格由 leverage、竞争、时机决定)」; (b) 估值与分析正典 (最标准化、最易蒸出高质量+CLI 化) — DCF (折现现金流: FCF 预测/WACC 折现率/terminal value 终值/Gordon growth vs exit multiple), Comparable Companies (可比公司/trading comps: EV/EBITDA, EV/Revenue, P/E), Precedent Transactions (先例交易/deal comps: control premium 控制权溢价), LBO (杠杆收购模型: IRR/MOIC/debt schedule/sources & uses), Accretion/Dilution (增厚/摊薄分析: EPS 影响、pro forma), Sum-of-the-Parts (分部估值/SOTP), Football Field (估值区间图), Merger Model (合并模型: synergies 协同/purchase accounting/goodwill), Sensitivity/scenario; (c) 交易流程与产出物 — 卖方流程 (sell-side: teaser 简介 → NDA → CIM/IM 信息备忘录 → management presentation → IOI 意向函 → data room 数据室 → LOI/term sheet → confirmatory diligence → SPA 买卖协议 → signing → closing), 买方流程 (buy-side: thesis/sourcing → outreach → valuation → bid → exclusivity → diligence → financing → close), auction 类型 (broad/targeted/negotiated/preemptive bid); 产出物: pitchbook 推介材料、CIM、fairness opinion 公平意见、board presentation、fee letter、engagement letter; (d) 交易结构与条款 — consideration (cash/stock/mix/earnout 对赌)、deal protections (breakup fee 分手费/go-shop/no-shop/MAC 重大不利变化条款)、representations & warranties 陈述与保证、escrow 托管、working capital adjustment 营运资金调整、reverse termination fee、collar 价格区间、tender offer vs merger、hostile vs friendly、defensive tactics (poison pill 毒丸/white knight 白衣骑士/staggered board); (e) 行业结构与角色 — bulge bracket (高盛/摩根士丹利/JPM/BofA/花旗) vs elite boutique (Centerview/Evercore/Moelis/Lazard/PJT/Perella) vs middle market (Houlihan Lokey/William Blair/Harris Williams) vs regional/independent; analyst→associate→VP→director→MD 晋升金字塔; coverage (行业组) vs product (M&A/ECM/DCM/leveraged finance/restructuring); sponsors group (服务 PE); 买方包括 PE/strategic acquirer/corp dev; (f) 量化指标与节奏 — deal fee (success fee 业内通常约 1-2% 视规模递减/retainer/Lehman formula)、league table 排行榜、pitch→mandate 转化、deal velocity、hours culture (analyst 80-100h/week 文化批判)、bonus/comp 结构、deal sheet (简历上的成交清单); (g) 争议/批判 — fairness opinion 是否橡皮图章 (利益冲突: 出意见的 banker 也收成交费)、estimate 的伪精确 (DCF garbage in garbage out、假设驱动结论)、banker 永远建议成交 (deal 偏见、empire building 助推 CEO 自利并购)、协同效应系统性高估 (大量并购毁灭价值、winner's curse 赢家诅咒)、analyst 血汗工厂文化 (2021 高盛 13 人 deck 事件、过劳死争议)、advisory 价值 vs 中介寻租之争、bulge vs boutique 的利益独立性叙事 (boutique 标榜「无承销利益冲突」)、SPAC 泡沫与 de-SPAC 教训; (h) 流派/思想谱系 — 估值学派 (Aswath Damodaran 估值教父/纽大、Tim Koller McKinsey《Valuation》、McKinsey valuation 体系) vs 公司金融教科书派 (Rosenbaum & Pearl《Investment Banking》行业圣经、Brealey Myers Allen、CFI/WSP/BIWS 培训体系) vs 交易实战派 (Bruce Wasserstein《Big Deal》、Joseph Perella/Felix Rohatyn 老派 dealmaker、现代 boutique 创始人) vs 行为/批判派 (并购毁灭价值的学术证据、Damodaran 对协同/控制权溢价的批判、Matt Levine《Money Stuff》解构华尔街逻辑) vs PE/buy-side 视角 (LBO 数学、value creation 杠杆/运营/multiple expansion)。不含: 二级市场股票交易/卖方研究 (equity research)、零售财富管理/private banking、纯 ECM/IPO 承销执行 (虽相关但聚焦 M&A advisory)、纯 PE 投后运营、量化交易/对冲基金策略、纯公司财务报表会计。) Master OS — automated mastery of 投行并购 / 交易撮合 (Investment Banking M&A / Dealmaking) — 面向并购顾问、企业融资、卖方/买方交易执行的职业认知操作系统，从业者(分析师 Analyst / 经理 Associate / 副总裁 VP / 董事 Director / 董事总经理 MD / 内部公司发展 Corp Dev / PE 投资人)、想入行者、以及服务这行(法律/会计/估值/咨询)的视角。覆盖: (a) 第一性张力 — 投行 M&A 的核心世界观分歧: **价格 vs 价值 (price 是市场愿意付的, value 是内在的, deal 在两者缝隙里成交) ⇄ 确定性 vs 最高价 (certainty of close 对卖方常胜过纸面最高报价) ⇄ 顾问/中介 vs 委托代理 (banker 是 agent, 客户利益 vs 成交费的激励冲突真实存在, 「banker 总想成交」是行业原罪批判)**; 更深层 — 「过程/竞价纪律 (controlled auction 制造竞争张力、信息不对称管理) ⇄ 关系/信任 (rela
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。
Mandatory pre-code gate and definition-of-done for ANY Odoo change (add field, override method, inherit view/xpath, OWL/JS patch, wizard, cron, controller, report, security, migration, bug fix, refactor, "optimize", "clean code", "stick to base"), Odoo 16-19. Also when the user pastes an Odoo traceback or install/upgrade error (ParseError "cannot be located in parent view", "Field ... does not exist", missing xmlid) or asks where an Odoo model, field, method, view or xmlid is defined. Run BEFORE brainstorming or planning: Odoo design questions are answered by tracing the real source into a Context Brief (file:line), not by open-ended Q&A or memory. Resolves the Odoo runtime and version, loads the matching odoo-<major> pack, and closes with install, test, upgrade, i18n, security and hygiene checks before commit.
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。
SERP-based semantic topic clustering for content architecture planning. Groups keywords by actual Google SERP overlap (not text similarity), designs hub-and-spoke content clusters with internal link matrices, and generates interactive visualizations. Optionally executes content creation if claude-blog is installed. Use when user says "topic cluster", "content cluster", "semantic clustering", "pillar page", "hub and spoke", "content architecture", "keyword grouping", or "cluster plan".
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。
Keep dependencies up-to-date. Discovers outdated deps via dependabot alerts/PRs, creates one PR per ecosystem, iterates until CI is green, then assigns for 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。
Turns open-ended requests into things to think WITH instead of answers to accept. Audits the hidden assumptions inside a topic, inverts them into sharp "what if" provocations, branches each one outward, and delivers a mind map plus written wonderings. Portable version, no vendor-specific tools required, works on any conversational assistant. Fire this when the person signals they want to open up a space and think alongside the assistant: "wonder about X", "what are the weird angles on X", "help me think about what this could be", "I want to explore, not decide yet". Do NOT fire when the same topic is attached to a request for concrete, usable, or decided output: a named deliverable, a count ("give me 5 names"), a deadline, or a "which / what should I pick" question. When it is genuinely unclear which they want, this skill opens by asking one line rather than branching. Not for factual lookups or executing a plan already chosen.
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。
Turns open-ended requests into things to think WITH instead of answers to accept. Audits the hidden assumptions inside a topic, inverts them into sharp "what if" provocations, branches each one outward, and delivers a fully-expanded mind map image plus the written wonderings. Fire this when the person signals they want to open up a space and think alongside you — "wonder about X", "what are the weird angles on X", "help me think about what this could be", "I want to explore, not decide yet" — or when they invoke /wonder or /wonderpill. Do NOT fire when the same topic is attached to a request for concrete, usable, or decided output: a named deliverable, a count ("give me 5 names"), a deadline ("ideas I can ship this week"), or a "which / what should I pick" question — those want straight answers, not a wonder pill. When it is genuinely unclear which they want, this skill opens by asking one line rather than branching. Not for factual lookups or executing a plan already chosen.
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。
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.
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。
This skill applies the analytical frameworks of Ronald C. Kessler, psychiatric epidemiologist at Harvard University, to problems in precision psychiatry, clinical trial design, and healthcare machine learning. Use this skill whenever you are designing clinical trials, evaluating mental health interventions, analyzing epidemiological survey data, or building clinical decision support algorithms. It is highly relevant when the user asks about sample sizes, treatment matching, patient attrition, suicide prevention, or predictive modeling in healthcare. Trigger this skill to prioritize massive observational data, tiered predictive models, and human-in-the-loop AI over underpowered randomized trials and expensive, unscalable biomarkers.
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。
Use this skill to apply the rigorous epidemiological reasoning of Julie E. Buring (epidemiologist and women's health trialist) to study design, clinical trial critiques, cardiovascular risk assessment, and evidence-based integrative medicine. Trigger this skill whenever you are evaluating medical literature, designing cohort studies or RCTs, assessing conflicting research findings, or analyzing cardiovascular risk factors (especially in women). Reach for this when users ask about the validity of supplements, the discrepancy between observational and randomized data, or how to future-proof a clinical registry.
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-affiliated in-product monetization design for paywall screens, feature gates, trial-expiry states, usage-limit prompts, and free-to-paid upgrade moments. Use when the user needs trigger timing, message structure, plan presentation, or experiment design after users have experienced value. NOT FOR: public pricing pages (use suede-site-alchemy), tier architecture (use suede-pricing), or cancellation and save flows (use suede-churn-prevention).
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 measurement discipline for tracking plans, event and conversion instrumentation, UTM and campaign-parameter hygiene, and verification of what actually fires. Use when setting up, auditing, or repairing analytics across web, product, paid, and lifecycle surfaces. NOT FOR: experiment design or significance decisions (use suede-ab-testing), campaign optimization (use suede-ads), attribution models, model comparison, or cross-tool reconciliation (use suede-attribution), or revenue-process architecture (use suede-revops).
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。
Review UI designs and implementations for accessibility, consistency, usability, and visual quality. Use when asked to review a design, audit accessibility, check UI consistency, compare implementation against mockups, or evaluate a user interface.
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。
Fetch up-to-date documentation for any library, framework, API, or service into context. Use when the user wants to look up API references, check function signatures or required fields, find feature-specific docs, or verify how an external tool actually works. Triggers for queries about third-party libraries like Stripe, SQLAlchemy, Tailwind, FastAPI, shadcn, Drizzle, Hono, Better Auth — any time the answer lives in official docs rather than in the project codebase. Use this instead of guessing from trained knowledge, which is stale.
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。
Use this skill for any Python backend work in this project: building FastAPI endpoints, writing service functions, defining Pydantic/SQLModel schemas, running Alembic migrations, or debugging 422 errors. Essential for authentication and authorization patterns — setting up get_current_user, is_superuser checks, admin-only guards, role-based access, and dependency injection chains like Depends(). Also covers middleware, background tasks, async SQLAlchemy sessions, ORM relationship loading, and request/response design. Activate whenever the question involves Python API code, FastAPI patterns, or backend architecture in this codebase. Not for frontend, Docker, CI/CD, or infrastructure.
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。
Design, review, and refactor Neo4j graph data models. Use when choosing node labels vs relationship types vs properties, migrating relational/document schemas to graph, detecting anti-patterns (generic labels, supernodes, missing constraints), designing intermediate nodes for n-ary relationships, enforcing schema with constraints and indexes, or assessing an existing model against graph modeling best practices. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle Spring Data Neo4j entity mapping — use neo4j-spring-data-skill. Does NOT handle GraphQL type definitions — use neo4j-graphql-skill. Does NOT handle data import — use neo4j-import-skill.
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。