「discovery」の検索結果

Use this skill when an admin needs to create an Einstein Discovery story in CRM Analytics Studio, configure prediction definitions, deploy writeback fields, set up what-if analysis, or manage model refresh and activation. Trigger keywords: Einstein Discovery story, prediction definition, writeback field, CRM Analytics Studio, model refresh, what-if analysis, bulk scoring, prediction field, 1OR prefix. NOT for the Einstein Discovery Flow action or model-health monitoring in Model Manager — use admin/einstein-discovery-deployment. NOT for Einstein Prediction Builder, a separate product needing no CRM Analytics license — use agentforce/einstein-prediction-builder. NOT for programmatic scoring through the Connect REST API — use agentforce/einstein-discovery-development.

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Use this skill when deploying a trained Einstein Discovery model to production records declaratively — activating a prediction definition, mapping output fields to page layouts, adding the Einstein Discovery Action to a Flow, running bulk predict jobs, and monitoring model health via Model Manager UI. Trigger keywords: prediction definition activation, bulk predict job, Einstein Discovery Flow action, Model Manager, prediction field mapping, model refresh activation, scoring job, Einstein Discovery recommendations on record. NOT for authoring the story in CRM Analytics Studio — use admin/einstein-discovery-setup. NOT for programmatic scoring through the API — use agentforce/einstein-discovery-development.

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Structure and prepare for a sales discovery call. Use when the user says "prep for discovery call", "discovery call questions", "how to structure my discovery call", "first call with a prospect", "what to ask on a discovery call", "sales call prep", "plan my discovery call", "initial call framework", or wants to prepare for or debrief a first sales conversation.

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[omh] Unvalidated early product idea: test whether a customer problem, segment, and business hypothesis deserve product investment, ending in kill, pivot, persevere, or inconclusive before any PRD. Use when the user says: product-discovery-validation, product discovery validation, product discovery, customer discovery, customer discovery plan, zero to one validation, validate the problem before building, problem solution interview.

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Establish weekly customer-discovery cadence and Opportunity Solution Tree practice using Teresa Torres's Continuous Discovery Habits framework during PRD v1.0 Market Adoption. Triggers on requests to set up discovery cadence, build opportunity solution tree, run weekly customer interviews, or when user asks "Torres", "continuous discovery", "opportunity solution tree", "outcomes vs outputs", "weekly interviews", "assumption mapping". Outputs CFD-* discovery entries and updates to ADO-STAGE-* and PER-* with new evidence.

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プロジェクトのゴール台帳（registry/goals/<owner>/<repo>.md）を人間と対話して新規作成・改訂する。 README と open Issue からゴール候補を推定して提示し、「何を目指すか」「何が起きていたら未達か」を 短く質問して条項を固め、書式検証（tools/work_discovery_goals.py validate）を通してから保存する。 「ゴール台帳を書きたい」「ゴールを設定して」「ゴール未設定と出た」「台帳エラーを直して」 「このプロジェクトの目標を決めたい」等や、/work-discovery の「ゴール未設定」「ゴール台帳エラー」案内を 受けて窓口が起動する。候補の提示そのものは /work-discovery の役目で本スキルではない。

NOTE: molecule and target inputs and your NGC_API_KEY are transmitted to external NVIDIA-hosted API endpoints on every call. Use local NIM containers for confidential or proprietary data. Run a complete computational drug discovery pipeline using NVIDIA BioNeMo NIMs: generate drug-like molecules with GenMol, dock them to a protein target with DiffDock, then predict binding affinity with Boltz2. Use this skill whenever the user wants to generate and screen small molecule drug candidates, perform hit discovery, optimize leads against a protein target, or do virtual screening combining molecule generation, docking, and affinity prediction. Triggers on: drug discovery pipeline, hit discovery, lead optimization, virtual screening, molecule generation, molecular docking, binding affinity, GenMol, DiffDock, Boltz2, SMILES, SAFE notation, NIM microservice. This is a multi-step pipeline composing three BioNeMo NIMs.

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Build empowered product teams using discovery and delivery dual-track. Use when the user mentions "product discovery", "empowered teams", "feature factory", "opportunity assessment", "product vision", "product strategy", "what should we build", or "our roadmap is just a feature list". Also trigger when restructuring teams away from output-driven models, or deciding what to build next based on outcomes. Covers discovery techniques, team structure, opportunity assessment, vision/strategy, and continuous delivery. For customer interviews, see mom-test. For ongoing discovery systems, see continuous-discovery.

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Implements automated PII discovery and classification using tools like Microsoft Purview, BigID, OneTrust DataDiscovery, and AWS Macie. Covers scanning schedules, accuracy tuning, false positive management, and integration patterns. Keywords: data discovery, PII scanning, Purview, BigID, Macie, OneTrust, automated classification, data cataloging.

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Expert discovery call strategist for B2B sales. Use when preparing for discovery calls, qualifying prospects, asking effective questions, identifying pain points, mapping stakeholders, or documenting findings. Covers SPIN selling, active listening, budget/timeline qualification, competition discovery, and CRM documentation. Use for sales qualification, needs analysis, and discovery call execution.

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プロダクトの基盤情報（課題仮説・ソリューション・市場スコープ・原体験・ビジネスモデル・競合・差別化）を ユーザーとの対話で掘り下げ、構造化されたドキュメント（product-context.md）として整理するスキル。 「自分のプロダクトって結局何なの？」を一緒に整理する壁打ち相手として機能する。 ペルソナ作成、LP設計、機能優先順位、マーケティング戦略など、 プロダクトの方向性に関わるあらゆる意思決定の「前提情報」を1ファイルにまとめる。 コードベースがあれば自動で読み取れる部分は埋め、残りをユーザーにヒアリングする。 Use when: 「プロダクトを整理したい」「ターゲット整理」「コンテキスト作成」 「ペルソナの前に」「誰向けのプロダクトか整理」「プロダクト情報まとめ」 「product context」「プロダクト定義」「プロダクトの前提」 「product discovery」「誰向け」と言われた時。 新しいプロジェクトの立ち上げ時や、方向性を見直したい時にも使う。 ペルソナ作成スキルを使う前に、まずこのスキルでプロダクトの前提を整理すべき。 Triggers: "product discovery", "product context", "プロダクト整理", "ターゲット整理", "コンテキスト作成", "プロダクト定義", "プロダクトの前提", "ペルソナの前に", "誰向け", "プロダクト情報まとめ", "プロダクトって何", "何を作ってるか整理", "どんな需要があるか"

Run product discovery to identify what to build. Use when the user says "product discovery", "how do I know what to build", "validate this idea", "talk to customers", "are we building the right thing", "discovery process", or wants to reduce the risk of building something users don't want - even if they don't say "discovery".

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Designing data stories and narrative-driven analytics in Salesforce: structuring CRM Analytics dashboards for executive communication, text widgets and conditional highlights for annotation, sequential narrative in Tableau Story sheets, and Einstein Discovery narrative REST endpoints. Trigger keywords: data storytelling dashboard, executive analytics narrative, CRM Analytics text widget annotation, Tableau story sheet, smart data discovery narrative API. NOT for building the Einstein Discovery story or prediction definition - use admin/einstein-discovery-setup. NOT for choosing between Reports, CRM Analytics and Tableau - use admin/einstein-analytics-basics.

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Design discovery, directories, and guilds for agent swarms at scale. Use when agents need to find each other on a shared surface: capability indices, yellow-pages directories, whois/phonebook routing, reputation-aware discovery, and guild structures that scope trust. Covers the canonical prior art (FIPA Directory Facilitator, Contract Net, Chord/DHT, DNS-SD/Consul, EigenTrust, Greif's merchant guilds) and the failure modes (read-poverty, Sybil reset, Goodhart on rank, directory staleness, cold-start). Triggers: "agents can't find each other", "who owns this file/skill", "route a question to the right agent", "capability registry", "agent reputation", "guild / federation of fleets". NOT for issuing identities, granting authority, or automatically assigning work from a directory entry.

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Use when coordinating product work across the 12 bundled product sub-skills (RICE, OKRs, UX research, design tokens, competitive teardown, analytics, experiments, discovery, roadmaps, spec-to-repo, landing pages, SaaS scaffolding) or the 4 standalone product-team plugins (user stories, Apple HIG, code-to-PRD, research summarizer). Triggers on 'help me prioritize', 'plan a product experiment', 'we ship features nobody uses', 'run the discovery loop', 'is our OST sound'. Forks context to route to one sub-skill via a deterministic signal router and returns a digest; can also drive a continuous-discovery loop (Torres cadence tracker + OST linter as machine gates) or a full goal→plan→execute→verify→close run through the repo-wide agent-harness. Distinct from project-management (how to deliver vs what to build), marketing/landing (from-scratch pages), and engineering/agent-harness (the generic loop engine this orchestrator plugs into).

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Build a weekly cadence of customer touchpoints using Opportunity Solution Trees, assumption mapping, and interview snapshots. Use when the user mentions "continuous discovery", "opportunity solution tree", "weekly interviews", "assumption testing", "discovery habits", "product trio", "outcome-based roadmap", "how do I talk to customers regularly", "we keep building things nobody uses", or "connect research to the roadmap". Also trigger when setting up regular customer feedback loops, prioritizing which experiments to run, or tying discovery insights to delivery work. Covers experience mapping, co-creation, and prioritizing opportunities. For interview technique, see mom-test. For team structure, see inspired-product.

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Run a consulting client discovery session — uncover the real problem, scope, and decision process. Use when asked to prepare for a client discovery call, qualify a consulting lead, scope an engagement, or run a kickoff. Produces a discovery plan — the questions that surface the real problem (not the stated one), budget/authority/timeline qualifiers, success criteria, red flags, and a follow-up that leads to a proposal.

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Expert knowledge for Azure Microsoft Discovery development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Discovery shared sessions, Bookshelf indexes, secure RBAC/CMK setups, REST jobs, or Docker-based tools, and other Azure Microsoft Discovery related development tasks. Not for Azure Portal (use azure-portal), Azure Resource Graph (use azure-resource-graph), Azure Monitor (use azure-monitor), Azure Cost Management (use azure-cost-management).

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This skill should be used when the user asks about "pantsing", "discovery write", "write without an outline", "discovery draft", "write into the dark", "story kernel", "reconcile a chapter", "dead end", "drafting sprint", "writing cadence", or wants to draft a story by discovery with retrospective bible reconciliation. NOT for outline-first drafting, or mysteries and other clue-dependent genres where setup must come before payoff (use chapter-writing), or a reverse outline of an existing linear draft, a subplot cut, or another revision pass on existing chapters (use revision-continuity).

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Influencer Discovery workflow skill. Use this skill when the user needs Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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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」) ⇄

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Use when creating or updating the project skill discovery config — generates or regenerates .dh/skill_discovery.yaml by scanning the repo to infer tech stack, inventorying installed skills via npx skills list, loading candidate skill content before suggesting, and writing a config-driven skill injection file. Triggers on /dh:setup-skill-discovery invocations and programmatic --auto calls from add-new-feature Phase 3.

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Expert product discovery guidance for user research and problem validation. Use when conducting user interviews, validating problems, applying jobs-to-be-done framework, sizing opportunities, customer segmentation, competitive analysis, prototype testing, usability testing, designing surveys, or synthesizing research insights. Covers discovery sprints, continuous discovery, and research operations.

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Product Discovery through an 18-task methodology in 6 blocks — from market analysis to an investor-ready financial plan. Use when someone wants to run Product Discovery, validate a startup, assess a market hypothesis, prepare for an investment round, or raises an adjacent topic — idea validation, niche sizing, competitor teardown, product-market fit, pitch preparation, startup unit economics, geographic expansion into a new country, go-to-market for SEA / Asia / MENA. People rarely name PD explicitly; they say 'is there a market for this', 'assess my idea', 'I need a deck for an angel', 'we are entering Thailand/Singapore/UAE, how do we size it'. Use the skill in those cases too. Three modes: Light (~45 min, idea stage), Full (~2-3 h, MVP with customers), Geographic Expansion (~2 h, product entering a new geography). Produces 3-4 artifacts in /mnt/user-data/outputs/: one-pager.pptx, financial-plan.xlsx, presentation.pptx, optionally interview-guide.docx.

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