「prospect」の検索結果

Automate Apollo.io lead generation -- search organizations, discover contacts, enrich prospect data, manage contact stages, and build targeted outreach lists -- using natural language through the Composio MCP integration.

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。

Discover prospect companies from a structured OpenClaw search brief, including public search and user-authorized data sources, then output a conservative candidate list ready for lead screening.

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。

Find the first batch of foreign-trade prospect companies from public web, LinkedIn, and user-authorized data sources such as customs exports, trade show lists, association directories, CRM/Excel files, or historical customer data, then output a conservative, structured candidate list ready for lead screening.

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。

Enterprise-specific view across CopilotKit + AG-UI. "Enterprise" here = CopilotKit's COMMERCIAL surfaces (Premium / CopilotKit Enterprise / Intelligence Platform / paid tiers), NOT CopilotKit running inside a big company. Tracks the commercial product surfaces (from product-surface-scan — Enterprise Intelligence, Cloud, self-host license, threads/persistence tier, Inspector, premium UI/Angular SDK, analytics, security bundle, Slack/Teams), applies the free-vs-paid classifier to decide if an issue belongs here, surfaces cross-page product contradictions, and tracks enterprise questions/complaints, community-sourced prospects (with a sales owner), and enterprise reporters with prior-week trend. Elevated to the top of the weekly report. Runs standalone ("who's at enterprise this week") or invoked by weekly-report. Triggers on "enterprise report", "enterprise signals", "enterprise status", "who at enterprise this week".

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。

After a weekly report is built, diff it against the PRIOR report to find items that appear in BOTH weeks, then print the Owner (and prospect "Passed to") value recorded last week so it can be carried forward. Print-only — never edits the owner fields; Nathan verifies and re-tags in Notion. Invoked by weekly-report near the end, and standalone on "carry forward owners", "who owned this last week", "owner continuity".

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。

Skill de pesquisa profunda alimentado por NotebookLM MCP. Conduz pesquisa estruturada em múltiplas fontes (análise de mercado, inteligência competitiva, análise de tendências, pesquisa de prospects) usando Google NotebookLM como mecanismo de pesquisa, depois entrega briefs formatados e artefatos opcionais de estúdio (slides, podcasts de áudio, vídeos, infográficos, relatórios, mapas mentais).

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。

Auto-generate a professional, client-ready GEO service proposal from audit data. Creates a full proposal in markdown and PDF including executive summary, findings, recommended service packages (Basic/Standard/Premium), pricing, timeline, and terms. Use when user says "proposal", "proposta", "offerta", "preventivo", "generate proposal", or after completing a GEO audit for a prospect.

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。

Typosquat and malicious-package detection across installed dependencies (or a single prospective addition) — cross-checks AI-malware family intelligence, package-name similarity to known popular packages, low maintainer-health signals. Use when auditing a freshly-onboarded repo, vetting a single suspicious package, gating CI on supply-chain risk, or investigating an incident.

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。

Pre-fills a customer's or prospect's security or third-party risk questionnaire from the organisation's own answer sources (prior questionnaires, answer library, policies), returning one row per question with a draft answer marked Reused, Adapted, Missing or Routed, its source, date, scope match and owner, plus the Missing list by owner. Never invents an answer, certification or control and never submits. Use when the user asks to "pre-fill this security questionnaire", "take a first pass at the customer's due diligence form", "answer this vendor assessment from our previous responses", "populate the third-party risk questionnaire" or "which questions can we reuse answers for". Do not use for screening a vendor's own answers, use vendor-risk-screening-brief instead; for RFP or tender answers use rfp-response-drafter. Drafts for human review; never approves, authorises or signs 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。

当用户在设计促销、定价或折扣策略，需要让"省钱"感知最大化时调用此 skill。核心信号：用户在纠结"怎么呈现折扣更有吸引力""消费者会不会觉得划算""原价和折扣价该怎么标"。不适用于：纯成本核算、B2B大额复杂定价谈判、品牌溢价策略（与折扣无关）。关键触发：涉及"打折""促销""优惠""划算"等定价呈现决策的场景。

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。

Automate Apollo.io lead generation -- search organizations, discover contacts, enrich prospect data, manage contact stages, and build targeted outreach lists -- using natural language through the Comp

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。

When the user wants help with public relations, earned media, press coverage, journalist outreach, or media strategy (not pull requests). Also use when the user mentions 'PR,' 'public relations,' 'press,' 'press release,' 'press coverage,' 'media outreach,' 'pitch a journalist,' 'get featured,' 'media list,' 'media kit,' 'press kit,' 'newsjacking,' 'news hijack,' 'HARO,' 'Qwoted,' 'Featured,' 'Help A Reporter,' 'reporter request,' 'tech press,' 'TechCrunch,' 'earned media,' 'thought leadership placement,' 'op-ed,' 'guest article,' 'press contacts,' or 'how do I get press.' Use this for earned media work — finding journalists, pitching stories, newsjacking, and responding to press requests. For startup/SaaS/AI directory submissions, see directory-submissions. For product launches, see launch. For social-media engagement, see social. For cold-email outreach to prospects, see cold-email.

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。

Send a box of Krispy Kreme donuts (doughnuts) to someone by mail, paid with your own credit card via Stripe Link — driven entirely from the terminal. Use when the user wants to send donuts, doughnuts, treats, or a thank-you gift to a lead, prospect, customer, colleague, or friend — e.g. "send donuts to Jane at Acme", "mail a dozen glazed to our new customer", "send a thank-you gift to the team". Orders are placed and shipped through the Zinc API; payment is a Stripe Link Shared Payment Token via the create-payment-credential (link-cli) 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。

Send a box of Krispy Kreme donuts (doughnuts) to someone by mail, paid with your own credit card via Stripe Link — driven entirely from the terminal. Use when the user wants to send donuts, doughnuts, treats, or a thank-you gift to a lead, prospect, customer, colleague, or friend — e.g. "send donuts to Jane at Acme", "mail a dozen glazed to our new customer", "send a thank-you gift to the team". Orders are placed and shipped through the Zinc API; payment is a Stripe Link Shared Payment Token via the create-payment-credential (link-cli) 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。

Generates B2B/B2C leads by scraping Google Maps, websites, Instagram, TikTok, Facebook, LinkedIn, YouTube, and Google Search. Use when user asks to find leads, prospects, businesses, build lead lis...

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。

Run a Busabase-backed sales prospecting and first-touch outreach desk with a bundled Hono App-in-Skill deployable to AirApp. Use whenever the user invokes $kelly-sales-outreach or /kelly-sales-outreach, wants to enter a product or service and discover its ideal customers, asks to continuously find target accounts or public business contacts, needs evidence-based ICP scoring and personalized outreach drafts, or wants to review and send cold outreach safely. Four subcommands - setup, profile, research, send - plus the desk itself. Every first-touch message requires human approval; one company receives one initial email; guessed addresses, purchased lists, secret exposure, automated spam, and unreviewed external sends are forbidden.

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 and maintains competitive battlecards from win/loss data, competitor intel, G2 reviews, and sales feedback. Use when building battlecards for a specific competitor, updating existing battlecards with new intel, preparing BDRs or AEs for competitive deals, analyzing win/loss patterns against a competitor, or responding to a competitor's product launch or pricing change. Also use when asked to "build a battlecard," "update competitive intel," "how do we beat [competitor]," "what do we say when a prospect mentions [competitor]," or "analyze our win/loss against [competitor]." Designed for B2B SaaS teams selling against known competitors in deals with multi-persona buying committees.

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。

Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda window scheduling, soft-core potentials, REST2 enhanced sampling, MBAR/BAR analysis, and cycle closure validation. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.

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。

Builds QSAR / QSPR models using chemprop D-MPNN, MolFormer, Uni-Mol, ChemBERTa, random forest baselines, and Gaussian processes with explicit handling of OECD 5 principles, applicability domain (kNN, leverage, conformal prediction, Mahalanobis), scaffold-balanced splits, ensemble uncertainty, calibration (Platt, isotonic), feature importance (SHAP, atomic attribution), and prospective validation. Use when building target-specific predictive models from in-house bioassay data, ADMET endpoints, or selectivity profiles.

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。

Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape + color), shape vs ECFP4 complementarity, conformer-ensemble searching, alignment optimization, and scaffold hopping. Use when searching for shape-mimicking compounds with different scaffolds, identifying bioisosteric replacements, prospective scaffold hopping, or expanding hit series beyond 2D similarity.

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。

Builds QSAR / QSPR models using chemprop D-MPNN, MolFormer, Uni-Mol, ChemBERTa, random forest baselines, and Gaussian processes with explicit handling of OECD 5 principles, applicability domain (kNN, leverage, conformal prediction, Mahalanobis), scaffold-balanced splits, ensemble uncertainty, calibration (Platt, isotonic), feature importance (SHAP, atomic attribution), and prospective validation. Use when building target-specific predictive models from in-house bioassay data, ADMET endpoints, or selectivity profiles.

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。

Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape + color), shape vs ECFP4 complementarity, conformer-ensemble searching, alignment optimization, and scaffold hopping. Use when searching for shape-mimicking compounds with different scaffolds, identifying bioisosteric replacements, prospective scaffold hopping, or expanding hit series beyond 2D similarity.

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。

Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda window scheduling, soft-core potentials, REST2 enhanced sampling, MBAR/BAR analysis, and cycle closure validation. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.

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。

Run a pre-mortem — imagine the project has already failed one year from now and work backward to find the root causes before they happen. Load when the user asks for a pre-mortem, wants to imagine failure before committing, asks "what could go wrong before we start", "assume this fails — why", "risk analysis before launch", "what kills this project", "what could go wrong", or when deep-thinking diagnoses a pre-mortem frame. Based on Gary Klein's prospective hindsight method, which surfaces failure causes more effectively than forward risk analysis. Most useful right before a major commitment.

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。