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Write SQL that uses BigQuery’s built-in machine learning and generative AI for forecasting, anomaly detection, identifying drivers of change, searching by meaning, and classifying or summarizing text stored in your data.
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Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.
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Build deterministic forecast scripts with Earth2Studio (model, data source, IO, inference). Do NOT use for ensemble, diagnostics, data-only fetch, or install.
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Create and validate Earth2Studio data source wrappers (DataSource, ForecastSource, DataFrameSource, ForecastFrameSource) from remote stores. Do NOT use for fetching data with existing sources, model inference, or installation tasks.
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Forecast Azure spend and price planned resources or workloads. WHEN: "forecast Azure spending", "project next month cost", "compare forecast to my planning target", "how much will Azure cost", "estimate VM cost", "compare storage tiers", "compare Azure regions", "retail price", "EA rate card", "negotiated pricesheet". DO NOT USE FOR: configured budget health or alerts, bill analysis, cost spikes, rightsizing, or commitments.
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How to produce a demand forecast for a SKU, and when to delegate that to a subagent vs. compute it yourself. Load this for any task involving "forecast", "how much will we sell", "next month", promos, or seasonal SKUs.
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Forecast Azure spend and price planned resources or workloads. WHEN: "forecast Azure spending", "project next month cost", "compare forecast to my planning target", "how much will Azure cost", "estimate VM cost", "compare storage tiers", "compare Azure regions", "retail price", "EA rate card", "negotiated pricesheet". DO NOT USE FOR: configured budget health or alerts, bill analysis, cost spikes, rightsizing, or commitments.
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Forecast cash flow and runway for a Well workspace from booked invoices and collected bank transactions. Use when the user asks for a cash-flow forecast, runway, how long until they run out of cash, projected balance, or expected inflows/outflows.
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Use Chronos Forecasting for pretrained time-series forecasting, Chronos-2 covariates, data validation, fine-tuning, evaluation, and deployment planning.
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Master the AI tools that transform financial operations. From bookkeeping to forecasting, manage money smarter and make data-driven financial decisions. Use when "finance, accounting, budgeting, forecasting, FP&A, bookkeeping, expense management, finance, accounting, budgeting, forecasting, fpa, expenses" mentioned.
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Records hypotheses, evidence and decisions when proposing, running or evaluating forecast experiments, including backtests and feature or model comparisons. Excludes routine tests and unchanged forecast operation.
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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.
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Build AI time series forecasting systems. TRIGGERS - Use when user needs help with ai-forecasting-system related tasks.
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Build AI demand forecasting systems. TRIGGERS - Use when user needs help with ai-demand-forecaster related tasks.
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Generate a weighted sales forecast with best/likely/worst scenarios, commit vs. upside breakdown, and gap analysis. Use when preparing a quarterly forecast call, assessing gap-to-quota from a pipeline CSV, deciding which deals to commit vs. call upside, or checking pipeline coverage against your number.
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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, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.
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Analyze sales pipeline, historical revenue, conversion rates, and assumptions to produce forecast scenarios. Use for sales reviews, RevOps planning, and founder revenue forecasting.
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Build and maintain a rolling financial forecast using a 12–18 month horizon. Lock actuals, reforecast remaining periods, extend the planning window, and generate a waterfall bridge showing prior-to-new variance. Use monthly or quarterly when the organization follows a continuous planning cadence instead of annual budgets.
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Audit demand forecasting models and inventory optimization logic -- forecast accuracy (MAPE, bias), safety stock calculations, reorder point strategies (EOQ, ROP, min/max), ABC/XYZ classification, demand signal pipelines, and multi-location network optimization..
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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'.
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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'.
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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.
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