320 件 ・ 関連度順
概要と使いどころ
Analyze demand forecasting systems — time-series decomposition (ARIMA, Prophet, ETS), seasonal and event-driven demand modeling, booking curve and pickup analysis, cancellation prediction, forecast accuracy metrics (MAPE, bias), and model retraining pipelines.
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Use when configuring or troubleshooting Salesforce Enterprise Territory Management (ETM): territory models, territory types, territory hierarchies, account assignment rules, opportunity territory assignment, and forecast by territory. Trigger keywords: territory model, territory hierarchy, ETM, assign accounts to territories, territory forecast, territory activation. NOT for choosing the coverage model first — use admin/territory-design-requirements. NOT for role hierarchy — use admin/sharing-and-visibility. NOT for Field Service ServiceTerritory — use admin/fsl-service-territory-setup. Trigger keywords: Territory2, Territory2Model, Territory2Rule, territory2Model-meta.xml, ObjectTerritory2Association, UserTerritory2Association, territory assignment rule, run assignment rules, territory access level, Manage Territories permission.
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Use when constructing the finance-side forecast — top-down vs bottom-up shape, confidence bands, retro-loop. Triggers on 'build the forecast model', 'reconcile top-down with bottom-up'.
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 when constructing the forecast call — commit / best-case / pipeline categorisation, deal-level evidence test, accuracy retro-loop. Triggers on 'build the forecast', 'why does our commit miss'.
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。
Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why.
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。
Expert en budgétisation et prévisions (FP&A, variance analysis, rolling forecasts, DZ)
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。
Build, analyze, repair, and audit finance three-statement models and operating forecasts. Use when the user invokes $kelly-finance, asks for 财务三表, 三表模型, income statement, balance sheet, cash flow statement, forecast model, budget model, financial projections, FP&A model, SaaS/unit economics forecast, fundraising model, board finance pack, investor model, model checks, balance-sheet balancing, cash runway, working capital, capex/depreciation schedules, debt schedules, scenario/sensitivity cases, or Excel/Sheets-ready finance outputs.
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。
Build AI demand forecasting systems. TRIGGERS - Use when user needs help with ai-demand-forecaster related tasks.
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。
Build AI time series forecasting systems. TRIGGERS - Use when user needs help with ai-forecasting-system related tasks.
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。
Codified expertise for demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation at multi-location retailers. Informed by demand planners with 15+ years experience managing hundreds of SKUs. Includes forecasting method selection, ABC/XYZ analysis, seasonal transition management, and vendor negotiation frameworks. Use when forecasting demand, setting safety stock, planning replenishment, managing promotions, or optimizing inventory levels.
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 personalized daily horoscope forecasts from zodiac-today.com API based on natal chart calculations. Use when a user wants: (1) daily guidance on what activities to pursue or avoid, (2) life planning help — best days for interviews, travel, romance, important decisions, (3) energy/focus/luck/romance forecasts to optimize their schedule, (4) lucky colors and numbers for the day, (5) future date analysis for planning events, trips, or milestones (paid tiers). Triggers: horoscope, zodiac, star sign forecast, daily guidance, lucky day, best day to, astrology advice, what should I do today, is today a good day for, plan my week astrology. Required env: ZODIAC_API_KEY (hsk_ API key), ZODIAC_PROFILE_ID (birth chart profile ID). Collects sensitive PII (email, birth date, birth city) for natal chart — requires user consent.
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。
Revenue forecast from pipeline data with stage-weighted probability and sensitivity analysis
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。
損益計算書・貸借対照表・キャッシュフロー計算書を数式で連動させるExcelモデルを作ります。実績と予測の入力、前提を変えた比較、財務三表の整合性確認を段階的に進めます。
Supports multivariate severity assessment and exploratory endpoint-time score forecasting for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-based foRcast forecasting. Use when combining welfare readouts — body weight or weight loss, body temperature, clinical or nesting scores, biomarkers, activity, heart rate, burrowing, wheel running — into one severity score per animal per day, when asking which animals are at risk of reaching a humane endpoint at a specified future observation time, when defining attention/danger zones or thresholds on a severity scale by kernel density estimation, or when reporting severity for a 3Rs, refinement, animal-welfare, or EU Directive 2010/63/EU severity-assessment context. Covers directionality ("turned" variables), baseline normalization, reference sets, RELSA weights, ARIMA prediction intervals, and RMSE/PICP/MPIW evaluation.
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 evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds.
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Reconciles the accounting ledger (MYOB, NetSuite, QuickBooks, Xero, or Zoho Books) against PayPal, Shopify, Square, and Stripe settlements, flags transactions that need attention, suspicious duplicates, and missing receipts, then writes a plain-English P&L narrative and exports a close packet (xlsx + one-page PDF). This is the first link of the /close-month command; a request to close the month or the books routes there, and the command runs this skill before refreshing the forecast and distributing the packet. Use this skill directly only when the owner wants the reconciliation alone, with no forecast refresh and no distribution: "just reconcile, no packet," "what's missing from the books," "flag the duplicates and missing receipts," or "write the P&L narrative for this month."
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。
Closes the books and turns them into a decision as a three-link chain — month-end-prep reconciles the ledger against every connected payment processor and writes the P&L narrative, cash-flow-snapshot then refreshes the 30/60/90-day forecast off the newly closed numbers rather than raw ones, and report-builder publishes and distributes the close packet. Requires a ledger (MYOB, NetSuite, QuickBooks, Xero, or Zoho Books) and uses Gusto, PayPal, Ramp, Shopify, Square, and Stripe when connected, falling back to statement or CSV uploads. Trigger on "close the month," "month-end," "close the books," "reconcile," "send the close packet to my accountant," or when the owner asks why revenue or margin moved last month. An owner who wants only the reconciliation and its flags, with no forecast refresh and no packet distribution, routes to month-end-prep directly.
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。
Reads AR/AP, historical cash timing, and known fixed costs from the ledger (MYOB, NetSuite, QuickBooks, Xero, or Zoho Books) or from PayPal, Square, or Stripe — or a CSV upload — and produces a 30/60/90-day cash flow forecast with percentage-variance confidence bands and named risk flags. Delivers a chat summary and a downloadable XLSX. Use when the user asks "forecast my cash flow," "will I make payroll," mentions "runway," or says "cash crunch." Falls back to CSV upload when no connector is live.
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。
Advanced Scrum Master skill for data-driven agile team analysis and coaching. Use when the user asks about sprint planning, velocity tracking, retrospectives, standup facilitation, backlog grooming, story points, burndown charts, blocker resolution, or agile team health. Runs Python scripts to analyse sprint JSON exports from Jira or similar tools: velocity_analyzer.py for Monte Carlo sprint forecasting, sprint_health_scorer.py for multi-dimension health scoring, and retrospective_analyzer.py for action-item and theme tracking. Produces confidence-interval forecasts, health grade reports, and improvement-velocity trends for high-performing Scrum teams.
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 financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when analyzing financial statements, building valuation models, assessing budget variances, or constructing financial projections and forecasts. Also applicable when users mention financial modeling, cash flow analysis, company valuation, financial projections, or spreadsheet analysis.
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。
Revenue leadership for B2B SaaS companies. Revenue forecasting, sales model design, pricing strategy, net revenue retention, and sales team scaling. Use when designing the revenue engine, setting quotas, modeling NRR, evaluating pricing, building board forecasts, or when user mentions CRO, chief revenue officer, revenue strategy, sales model, ARR growth, NRR, expansion revenue, churn, pricing strategy, or sales capacity.
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。
Expert knowledge for AI forecasting — superforecasting principles, signal taxonomy, confidence calibration, reasoning chains, and accuracy tracking
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。
Calculate and model paid-media CPA, CPL, CPC, CPM, ROAS, MER, break-even targets, contribution margin, LTV:CAC, impression-share opportunity, budgets, forecasts, and experiment economics. Use for PPC math, ad calculator, break-even analysis, ROAS calculator, CPA calculator, budget forecast, LTV CAC, or MER.
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。
Plan and review paid-media budgets, bidding, pacing, marginal return, forecasts, CPA, ROAS, MER, LTV:CAC, constraints, and allocation across supported platforms. Use for ad budget allocation, media budget, bidding strategy, scaling, spend pacing, budget forecast, ROAS target, or investment tradeoffs.
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。