「rag」の検索結果

Comprehensive expertise in automated crypto trading systems, including DEX sniping bots, arbitrage strategies, MEV protection, Telegram trading bots, and anti-rug protection. Use when "trading bot, sniping bot, arbitrage bot, Telegram trading, DEX bot, MEV bot, copy trading, auto trading, token sniper, " mentioned.

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。

Generates a behavioral scenario acceptance matrix for comprehensive test coverage planning. Maps user scenarios to acceptance criteria with stable IDs. Use when planning test coverage for a complex feature, before a release or milestone review, or when someone asks what is tested.

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-engineer workflow skill. Use this skill when the user needs Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations 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 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-engineer workflow skill. Use this skill when the user needs Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations 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。

广告外包公司绩效管理 (广告外包公司绩效管理 (Ad Agency / Marketing-Outsourcing Firm Performance Management) — 广告/营销外包公司(乙方 agency:创意热店/4A/本土广告公司/传媒公司/数字营销代理/MCN/设计工作室/内容外包)的『怎么做绩效管理』职业认知操作系统,面向老板/合伙人、运营总监(COO)、HR/HRBP、项目总监、team lead、以及想搭绩效体系的从业者。覆盖: (a) 第一性张力 — 绩效管理的核心世界观分歧: **创意/知识工作『不可量化』 vs 『必须可考核』(创意难归因、难标准化,硬套 KPI 杀创意;但不考核养懒人——这是本行绩效的元矛盾) ⇄ 结果导向(KPI/业绩/回款) vs 过程导向(OKR/能力/成长) ⇄ 个人绩效 vs 团队协作(广告是集体产物,创意-AE-媒介-设计协作,难拆到个人) ⇄ 强激励(提成制:多劳多得但抢单/短视/不协作/吃老客户) vs 稳定(固定+奖金:公平但大锅饭) ⇄ 规模/流水 vs 利润/人效(低价接单冲规模 vs 保毛利)**; (b) 绩效体系设计 — KPI(关键指标法)/OKR(目标与关键成果)/BSC(平衡计分卡)/360 环评/MBO(目标管理)/KSF(关键成功因子)/积分制/计件提成;考核周期(月/季/年+项目制);绩效面谈、绩效改进 PIP、强制分布(271/活力曲线)争议、绩效结果应用(调薪/晋升/淘汰/奖金); (c) 分岗位绩效(本行难点,各岗量化差异极大) — 创意(文案/美术/创意总监:作品质量、获奖、比稿命中率——最难量化)、AE/客户执行(客户满意度、续约、回款、增购、客诉)、媒介/投放(可量化:ROI/ROAS/CPM/转化——最易量化)、策略/策划(方案通过率、洞察)、设计(产能/返稿率/品质)、项目管理(交付准时率、利润率)、销售/BD(新签、回款、毛利); (d) 项目与客户维度绩效(agency 特有,专业服务公司逻辑) — 项目利润率(收入-人力成本-外部成本)、工时制与人效(billability 可计费工时率/utilization 利用率/realization 实现率,借鉴咨询律所)、人均产值/人均毛利、客户续约率与 LTV、客户集中度风险、比稿投入产出、改稿次数失控; (e) 激励与分配机制 — 提成制(按签单/毛利/回款抽成)、项目奖金分成(如何在创意-AE-媒介间分)、年终奖包、合伙人制/事业合伙人/工作室 studio 制/阿米巴、股权期权、创意人才的非物质激励(署名/获奖/成长); (f) 人效、成本与文化 — 人效比(人力成本占收入比,业内估计通常 40-55%,非普适)、毛利率、加班/血汗工厂文化批判(乙方 996/改稿到凌晨)、人才流失率与保留、招聘与培养、组织架构(客户组 vs 职能组 vs 项目制矩阵); (g) 外包/乙方特有张力对绩效的侵蚀 — 甲乙方权力不对等(甲方压价、无限改稿、比稿白嫖创意、账期长垫款重回款难)、低价内卷与红海、项目制不确定性(旺淡季、大客户依赖)、创意工时不可控如何计入绩效、外包 vs 自建团队的成本对比; (h) 争议/批判 — KPI 量化派 vs 创意不可考核派、提成制养蛊 vs 团队协作、强制分布/末位淘汰是否适合小 agency、工时制(billable hours)被咨询律所验证但绑架员工健康、『向甲方看齐做 OKR』水土不服、绩效主义扼杀创意(索尼绩效主义之殇式批判)、乙方绩效本质是『用考核对冲甲方不确定性』的转嫁; (i) 流派/思想谱系 — 专业服务公司管理派(David Maister《Managing the Professional Service Firm》PSF 圣经:leverage 杠杆/utilization 利用率/billing;借鉴咨询律所会计所) vs agency 专家经营派(David C. Baker《The Business of Expertise》+2Bobs podcast、Blair Enns《Win Without Pitching》《Pricing Creativity》定位与定价) vs OKR/目标管理派(John Doerr《Measure What Matters》、Google/Intel OKR、字节/飞书 OKR 本土化) vs 中式绩效工具派(KSF 薪酬全绩效/积分制/阿米巴/华为绩效体系被广告公司借用) vs 本土 4A/广告公司实战派(省广/蓝色光标/华扬联众/利欧 等上市广告公司管理 + 创意热店工作室制)。不含: 广告投放/信息流/SEM 的技术操作本身、甲方市场部/品牌方内部绩效、通用 HR 招聘薪酬全流程(仅取与绩效相关部分)、纯财务会计做账、MCN 达人孵化运营细节。) Master OS — automated mastery of 广告外包公司绩效管理 (Ad Agency / Marketing-Outsourcing Firm Performance Management) — 广告/营销外包公司(乙方 agency:创意热店/4A/本土广告公司/传媒公司/数字营销代理/MCN/设计工作室/内容外包)的『怎么做绩效管理』职业认知操作系统,面向老板/合伙人、运营总监(COO)、HR/HRBP、项目总监、team lead、以及想搭绩效体系的从业者。覆盖: (a) 第一性张力 — 绩效管理的核心世界观分歧: **创意/知识工作『不可量化』 vs 『必须可考核』(创意难归因、难标准化,硬套 KPI 杀创意;但不考核养懒人——这是本行绩效的元矛盾) ⇄ 结果导向(KPI/业绩/回款) vs 过程导向(OKR/能力/成长) ⇄ 个人绩效 vs 团队协作(广告是集体产物,创意-AE-媒介-设计协作,难拆到个人) ⇄ 强激励(提成制:多劳多得但抢单/短视/不协作/吃老客户) vs 稳定(固定+奖金:公平但大锅饭) ⇄ 规模/流水 vs 利润/人效(低价接单冲规模 vs 保毛利)**; (b) 绩效体系设计 — KPI(关键指标法)/OKR(目标与关键成果)/BSC(平衡计分卡)/360 环评/MBO(目标管理)/KSF(关键成功因子)/积分制/计件提成;考核周期(月/季/年+项目制);绩效面谈、绩效改进 PIP、强制分布(271/活力曲线)争议、绩效结果应用(调薪/晋升/淘汰/奖金); (c) 分岗位绩效(本行难点,各岗量化差异极大) — 创意(文案/美术/创意总监:作品质量、获奖、比稿命中率——最难量化)、AE/客户执行(客户满意度、续约、回款、增购、客诉)、媒介/投放(可量化:ROI/ROAS/CPM/转化——最易量化)、策略/策划(方案通过率、洞察)、设计(产能/返稿率/品质)、项目管理(交付准时率、利润率)、销售/BD(新签、回款、毛利); (d) 项目与客户维度绩效(agency 特有,专业服务公司逻辑) — 项目利润率(收入-人力成本-外部成本)、工时制与人效(billability 可计费工时率/utilization 利用率/realization 实现率,借鉴咨询律所)、人均产值/人均毛利、客户续约率与 LTV、客户集中度风险、比稿投入产出、改稿次数失控; (e) 激励与分配机制 — 提成制(按签单/毛利/回款抽成)、项目奖金分成(如何在创意-AE-媒介间分)、年终奖包、合伙人制/事业合伙人/工作室 studio 制/阿米巴、股权期权、创意人才的非物质激励(署名/获奖/成长); (f) 人效、成本与文化 — 人效比(人力成本占收入比,业内估计通常 40-55%,非普适)、毛利率、加班/血汗工厂文化批判(乙方 996/改稿到凌晨)、人才流失率与保留、招聘与培养、组织架构(客户组 vs 职能组 vs 项目制矩阵); (g) 外包/乙方特有张力对绩效的侵蚀 — 甲乙方权力不对等(甲方压价、无限改稿、比稿白嫖创意、账期长垫款重回款难)、低价内卷与红海、项目制不确定性(旺淡季、大客户依赖)、创意工时不可控如何计入绩效、外包 vs 自建团队的成本对比; (h) 争议/批判 — KPI 量化派 vs 创意不可考核派、提成制养蛊 vs 团队协作、强制分布/末位淘汰是否适合小 agency、工时制(billable hours)被咨询律所验证但绑架员工健康、『向甲方看齐做 OKR』水土不服、绩效主义扼杀创意(索尼绩效主义之殇式批判)、乙方绩效本质是『用考核对冲甲方不确定性』的转嫁; (i) 流派/思想谱系 — 专业服务公司管理派(David Maister《Managing the Professional Service Firm》PSF 圣经:leverage 杠杆/utilization 利用率/billing;借鉴咨询律所会计所) vs agency 专家经营派(David C. Baker《The Business of Expertise》+2Bobs podcast、Blair Enns《Win Without Pitching》《Pricing Creativity》定位与定价) vs OKR/目标管理派(John Doerr《Measure What Matters》、Google/Intel OKR、字节/飞书 OKR 本土化) vs 中式绩效工具派(KSF 薪酬全绩效/积分制/阿米巴/华为绩效体系被广告公司借用) vs 本土 4A/广告公司实战派(省广/蓝色光标/华扬联众/利欧 等上市广告公司管理 +

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。

管理咨询 (管理咨询 (Management Consulting) — 战略与管理咨询的职业认知操作系统，从业者/咨询顾问/想入行者/采购咨询服务的客户视角。覆盖: (a) 第一性张力 — 假设驱动 (hypothesis-driven / answer-first / Day-1 answer) 的「先有答案再验证」⇄ 数据驱动 (data-led / bottom-up) 的「先穷尽事实再归纳」，这行的核心张力是「先射箭再画靶 vs 先画靶再射箭」，资深人偏 top-down 假设树减少 boil-the-ocean，但要时刻防 confirmation bias; 以及更深层的张力 — 「卖洞见 (insight / so-what) vs 卖工时 (analysis / 体力)」，「客户影响 (client impact / 落地) vs 智识严谨 (intellectual rigor / 漂亮 deck)」; (b) 方法论正典 (最标准化、最易蒸出高质量) — MECE (相互独立完全穷尽)、issue tree / logic tree (问题树/逻辑树)、hypothesis-driven problem solving (假设驱动)、Pyramid Principle (Minto 金字塔原理: SCQA 情境-冲突-疑问-回答 + 结论先行 + 自上而下 + 归纳/演绎)、80/20 (帕累托/抓大放小)、so-what (所以呢/洞见提炼)、storyline (故事线/ghost deck 鬼影稿)、driver tree / profit tree、2x2 矩阵、value chain、frameworks (Porter 五力/3C/4P/7S/BCG 矩阵/价值链) 既是脚手架也是陷阱 (套框架 vs 真洞见); (c) 行业结构 — MBB (McKinsey/BCG/Bain 战略三巨头) vs Big Four 咨询臂 (Deloitte/PwC Strategy&/EY-Parthenon/KPMG) vs 精品战略所 (Oliver Wyman/Kearney/Roland Berger/L.E.K./Arthur D. Little) vs 专业/职能 boutique (运营/数字化/PE 尽调); up-or-out (非升即走)、leverage model (杠杆模型: 1 个合伙人带多个 EM/咨询师/分析师的金字塔)、partner/principal/EM(项目经理)/associate(咨询师)/analyst(分析师) 职级; (d) 项目交付模型 (the case/study/engagement) — 提案/SOW (scope of work)、problem definition (问题定义/真问题 vs 表象问题)、workplan (工作计划)、hypothesis tree (假设树)、analysis (分析/建模)、synthesis (综合)、recommendation (建议)、implementation (落地); 客户管理 (steering committee 指导委员会、stakeholder 利益相关方、对齐); (e) 产出物 — the deck (PPT 幻灯片是咨询的母语)、executive summary、action title (行动标题/每页一句话结论)、ghost deck (先搭骨架后填数据)、Excel 财务模型、framework 图; (f) 职业/招聘 — case interview 生态 (案例面试: Victor Cheng LOMS/Case in Point/market sizing 市场估算/估算题/fit 行为面)、网申-笔试-案例面、up-or-out、exit options (退出路径: PE/VC/corp dev 企业发展/战略岗/创业/industry); (g) 争议/批判 — 咨询的价值之辩 (「借你的表告诉你时间」「frameworks 是剧场表演 vs 真洞见」Matthew Stewart《The Management Myth》)、McKinsey 的丑闻 (Purdue 阿片类/独裁政府/ICE/利益冲突, Bogdanich & Forsythe《When McKinsey Comes to Town》)、咨询 vs 自建战略部、generalist 通才 vs specialist 专才之争、AI/GenAI 对初级分析师工作的冲击; (h) 流派 — 战略经典 (Porter 定位学派/五力 vs 资源基础观 RBV vs 蓝海战略 Kim&Mauborgne vs 颠覆式创新 Christensen vs Mintzberg 应急战略批判 planning school); 三巨头气质分野 (McKinsey 事实驱动/CEO 信任/通才, BCG 概念/思想领导力/经验曲线/增长-份额矩阵, Bain 结果导向/NPS 净推荐值/PE 关系/与客户深度绑定)。不含: 投行 M&A/财务顾问 (估值/承销超出范畴)、纯 IT 实施/系统集成 (SI 人力外包)、纯审计/税务、纯人力 RPO/猎头、内部战略部 only (虽相关但本 skill 聚焦专业服务咨询的外部视角)。) Master OS — automated mastery of 管理咨询 (Management Consulting) — 战略与管理咨询的职业认知操作系统，从业者/咨询顾问/想入行者/采购咨询服务的客户视角。覆盖: (a) 第一性张力 — 假设驱动 (hypothesis-driven / answer-first / Day-1 answer) 的「先有答案再验证」⇄ 数据驱动 (data-led / bottom-up) 的「先穷尽事实再归纳」，这行的核心张力是「先射箭再画靶 vs 先画靶再射箭」，资深人偏 top-down 假设树减少 boil-the-ocean，但要时刻防 confirmation bias; 以及更深层的张力 — 「卖洞见 (insight / so-what) vs 卖工时 (analysis / 体力)」，「客户影响 (client impact / 落地) vs 智识严谨 (intellectual rigor / 漂亮 deck)」; (b) 方法论正典 (最标准化、最易蒸出高质量) — MECE (相互独立完全穷尽)、issue tree / logic tree (问题树/逻辑树)、hypothesis-driven problem solving (假设驱动)、Pyramid Principle (Minto 金字塔原理: SCQA 情境-冲突-疑问-回答 + 结论先行 + 自上而下 + 归纳/演绎)、80/20 (帕累托/抓大放小)、so-what (所以呢/洞见提炼)、storyline (故事线/ghost deck 鬼影稿)、driver tree / profit tree、2x2 矩阵、value chain、frameworks (Porter 五力/3C/4P/7S/BCG 矩阵/价值链) 既是脚手架也是陷阱 (套框架 vs 真洞见); (c) 行业结构 — MBB (McKinsey/BCG/Bain 战略三巨头) vs Big Four 咨询臂 (Deloitte/PwC Strategy&/EY-Parthenon/KPMG) vs 精品战略所 (Oliver Wyman/Kearney/Roland Berger/L.E.K./Arthur D. Little) vs 专业/职能 boutique (运营/数字化/PE 尽调); up-or-out (非升即走)、leverage model (杠杆模型: 1 个合伙人带多个 EM/咨询师/分析师的金字塔)、partner/principal/EM(项目经理)/associate(咨询师)/analyst(分析师) 职级; (d) 项目交付模型 (the case/study/engagement) — 提案/SOW (scope of work)、problem definition (问题定义/真问题 vs 表象问题)、workplan (工作计划)、hypothesis tree (假设树)、analysis (分析/建模)、synthesis (综合)、recommendation (建议)、implementation (落地); 客户管理 (steering committee 指导委员会、stakeholder 利益相关方、对齐); (e) 产出物 — the deck (PPT 幻灯片是咨询的母语)、executive summary、action title (行动标题/每页一句话结论)、ghost deck (先搭骨架后填数据)、Excel 财务模型、framework 图; (f) 职业/招聘 — case interview 生态 (案例面试: Victor Cheng LOMS/Case in Point/market sizing 市场估算/估算题/fit 行为面)、网申-笔试-案例面、up-or-out、exit options (退出路径: PE/VC/corp dev 企业发展/战略岗/创业/industry); (g) 争议/批判 — 咨询的

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。

DevOps 与站点可靠性工程 (SRE) — 平台 / 基础设施 / 可靠性工程师的认知操作系统, 覆盖软件交付 + 运维全生命周期 (CI/CD 与发布工程 trunk-based + 渐进式发布 canary/blue-green/feature flag + GitOps Argo CD/Flux / 基础设施即代码 Terraform/OpenTofu/Pulumi/Ansible + policy-as-code OPA / 容器与编排 Docker/Kubernetes + Helm/Kustomize + service mesh Istio/Linkerd / 可观测性 Prometheus + Loki + OpenTelemetry + Honeycomb + eBPF + RED/USE / SLO-SLI-error budget 与可靠性工程 Google SRE 学科 + 容量规划 + 优雅降级 / 事件管理与 on-call 事件指挥 + PagerDuty + runbook + 无指责复盘 + MTTR / 云平台与 FinOps AWS/GCP/Azure + 成本优化 + 弹性伸缩 / 平台工程与开发者体验 IDP + Backstage + golden path + Team Topologies / DevSecOps 与供应链安全 shift-left + SBOM + SLSA + sigstore + Vault / 韧性与混沌工程 fault injection + game day + 安全科学 / DORA 指标与工程效能 部署频率 + 变更前置时间 + 变更失败率 + Accelerate 研究 / 数据库与有状态运维 schema 迁移 + 备份容灾) — 不含 通用应用开发 / 纯云销售认证速成 / 'DevOps = 跑 Jenkins 的岗位' 窄化误解 / ITIL 工单文化传统运维 (旧范式仅做边界) / 把手工运维 ClickOps 当稳态 (是 toil, 本 skill 核心反模式) (DevOps & Site Reliability Engineering — the cognitive operating system of platform / infrastructure / reliability practitioners who own the full software delivery + operational lifecycle, covering (a) CI/CD & release engineering (build pipelines, trunk-based development, progressive delivery — canary / blue-green / feature flags, GitOps with Argo CD / Flux), (b) Infrastructure as Code (Terraform / OpenTofu, Pulumi, CloudFormation, Ansible, Crossplane — module design, state management, drift, policy-as-code OPA / Sentinel / Checkov), (c) containers & orchestration (Docker / OCI, Kubernetes — scheduling, networking CNI, storage CSI, operators / CRDs, Helm / Kustomize, service mesh Istio / Linkerd), (d) observability (the three pillars + beyond — metrics Prometheus / VictoriaMetrics, logs Loki / ELK, traces OpenTelemetry / Jaeger / Tempo, high-cardinality observability Honeycomb, eBPF, RED / USE methods, SLO-based alerting), (e) SLO / SLI / error budgets & reliability engineering (Google SRE discipline — service level objectives, error budget policy, toil budgets, capacity planning, load shedding, graceful degradation), (f) incident management & on-call (incident command, PagerDuty / Opsgenie, runbooks, blameless postmortems, MTTR / MTTD, error budget burn), (g) cloud platforms & FinOps (AWS / GCP / Azure well-architected, multi-region, cost optimization, autoscaling), (h) platform engineering & developer experience (internal developer platforms, Backstage, golden paths, self-service, Team Topologies), (i) DevSecOps & supply-chain security (shift-left, SAST / DAST, SBOM, SLSA, sigstore / cosign, secrets management Vault), (j) resilience & chaos engineering (chaos experiments, fault injection, game days, resilience engineering / safety science), (k) DORA metrics & engineering effectiveness (deployment frequency, lead time, change failure rate, MTTR, the Accelerate research), (l) databases & stateful operations (schema migrations, backups / DR, replication); NOT generic software development / app feature coding (是 平行学科, DevOps/SRE 关注 delivery + operability 不是 product feature), NOT pure cloud sales / certification cram without operational depth, NOT 'DevOps = a job title that runs Jenkins' 的窄化误解 (DevOps 是 文化 + 实践, SRE 是 Google 对 reliability 的工程化具体实现), NOT ITIL-heavy 传统运维 工单文化 (是 被 DevOps 取代的旧范式, 仅做边界标注), NOT manual ops / ClickOps as a steady state (是 toil, 本 skill 的核心反模式).) Master OS — automated mastery of DevOps & Site Reliability Engineering — the cognitive operating system of platform / infrastructure / reliability practitioners who own the full software delivery + operational lifecycle, covering (a) CI/CD & release engineering (build pipelines, trunk-based development, progressive delivery — canary / blue-green / feature flags, GitOps with Argo CD / Flux), (b) Infrastructure as Code (Terraform / OpenTofu, Pulumi, CloudFormation, Ansible, Crossplane — module design, state management, drift, policy-as-code OPA / Sentinel / Checkov), (c) containers & orchestration (Docker / OCI, Kubernetes — scheduling, networking CNI, storage CSI, operators / CRDs, He

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FLOW framework integration — evidence-led SEO using the Find → Leverage → Optimize → Win loop. Surfaces stage-specific AI prompts from the FLOW knowledge base (41 prompts, CC BY 4.0). Use when user says "FLOW", "FLOW framework", "seo flow", "evidence-led SEO", "find leverage optimize win", or wants stage-specific SEO prompts.

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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.

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Generate unit tests for untested branches and edge cases. Use when coverage is low, CI flags gaps, or a release needs hardening. Not for integration/E2E suites, framework migrations, or fixing production bugs.

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Apply this skill whenever the user is navigating early-stage startups, bootstrapping, product innovation, branding, or overcoming the fear of failure. Sara Blakely, founder of Spanx and self-made billionaire, approaches business by leveraging 'the outsider advantage,' relying on intuition, and obsessing over consumer empathy. Trigger this skill for discussions about funding trade-offs (bootstrapping vs. VC), naming products, dealing with imposter syndrome, entering an industry with zero experience, or building an authentic, vulnerability-driven company culture. Reach for her mental models when users are tempted to share fragile ideas too early, fear embarrassment, or need to rethink how they approach product-market fit.

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Applies the reasoning style of Daphne Koller (machine learning pioneer, co-founder of Coursera, founder and CEO of Insitro). Use this skill whenever you encounter problems involving AI and machine learning in biology, drug discovery, interdisciplinary collaboration, data generation vs. data mining, or transitioning from academia to industry. Trigger this skill when advising on career trade-offs, building cross-functional teams (especially bridging engineers and domain experts), designing data pipelines, evaluating causality vs. correlation, or applying AI to physical systems ('where bits meet atoms'). Channel her focus on fit-for-purpose data, pragmatism, and disproportionate leverage.

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Suede AI combined code review and ship grade in one pass: findings with file:line evidence plus an A-F lane grade, Instant-F security triggers, OWASP checks, a deploy-safety gate, and fix briefs. Use when asked to review this, grade this, security-check this, is this safe to ship, or check this PR before merge: whenever the caller wants both what is wrong and whether it ships. Runs only when explicitly invoked; never auto-fires on a diff, save, or commit. NOT FOR: findings only with accessibility and SEO lanes (use suede-code-review); the letter grade alone (use suede-code-grader); making CI enforce the verdict on merge (use suede-ci-gate); LLM, RAG, or agent behavior coverage (use suede-ai-eval).

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CRE Brokerage Investment Sales v1 - 8 specialist skills for U.S. seller-side commercial investment sales brokers, covering assignment intake, broker opinion of value, listing proposal, OM and teaser drafting, buyer process management, bid leveling, negotiation support, and PSA-to-close coordination.

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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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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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Use when adding or changing save games, settings or progression storage - a versioned save format with a tested migration chain, atomic writes with backup and checksum, per-engine storage locations, safe serializers, and the round-trip/migration/corruption tests.

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Expert PR and media relations guidance for earned media, press coverage, and reputation building. Use when writing press releases, crafting media pitches, developing journalist relationships, planning embargo strategies, managing crisis communication, placing thought leadership, building analyst relations, submitting award applications, or measuring PR coverage. Use for media outreach, press kits, speaking opportunities, and earned media strategy.

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用户考虑使用杠杆（保证金/贷款/融资）来放大投资回报，或评估财务安全性时。 语言信号:"要不要加杠杆"/"用保证金买""贷款投资划算吗"/"融资利率很低应该借钱投吗" 不适用于:不涉及杠杆/融资的纯经营决策。

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Manage Hyperliquid perp positions and margin from the desk computer - read positions and margin, set leverage and cross/isolated mode, add isolated margin, understand margin tiers and liquidation price, close a position with a reduce-only IOC, and clean up orphaned orders. Write actions are Execution Trader only, on an approved ticket. Use for leverage changes, closes, protection checks and margin questions.

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Analyze data coverage, create monitors for warehouse tables and AI agents. Covers coverage gaps, use-case analysis, data monitor creation, and agent observability.

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Analyze a warehouse for stale, unused, or redundant tables via the analyze_storage_costs MCP tool. Classifies waste patterns and table categories, computes safety tiers, and handles category drill-downs and lineage follow-ups.

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Guide users from coverage analysis to monitor creation. USE WHEN user asks what should I monitor, where are my gaps, improve coverage, or wants a systematic approach to monitoring across their data estate.

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