347 skills · sorted by relevance
Analyze time series with aeon, a Python toolkit for data that changes over time. Supports classification, regression, clustering, forecasting, anomaly detection, and pattern search, with guidance on preprocessing, algorithm selection, and evaluation.
Build formula-driven Excel financial models for linked financial statements, business valuation, and fundraising forecasts. Separate assumptions, calculations, and results, compare scenarios, and check that statement balances and saved calculation results are consistent.
Coordinate month-end reconciliation, owner sign-off, and a 30/60/90-day cash forecast based on closed books. Combine the results into a reporting packet with financial explanations and open items, with approval required before external delivery.
Adds a one-line safety note before weather forecasts involving storms, flooding, extreme temperatures, or high winds. Uses a reference file to determine which conditions qualify as hazardous and need a warning.
Analyze sprint history to forecast delivery ranges, score team health, and track retrospective actions. Python tools turn structured sprint data into reports that support planning, highlight recurring problems, and show whether improvement efforts are progressing.
Plan revenue growth for B2B SaaS businesses by analyzing sales opportunities, pricing, customer retention, and sales capacity. Develop scenario forecasts, churn intervention plans, hiring models, and revenue reporting for board discussions.
Calculate advertising costs, revenue relative to ad spend, break-even targets, and budget forecasts. The skill makes inputs and formulas explicit, checks inconsistent data, and compares base, downside, and upside scenarios when uncertainty affects the decision.
Check current weather and forecasts for a city, region, airport code, or coordinates. Summarize conditions, temperature, rain, and wind using an available web tool or wttr.in to help plan outings and travel.
Guide economic time series analysis from initial plots to forecasting. Use Python, R, and Stata examples to check whether statistical properties remain stable over time, choose models, diagnose errors, and examine relationships between multiple series.
Zero-shot time series forecasting with Google's TimesFM foundation model. Use this skill when forecasting ANY univariate time series — sales, sensor readings, stock prices, energy demand, patient vitals, weather, or scientific measurements — without training a custom model. Automatically checks system RAM/GPU before loading the model, supports CSV/DataFrame/array inputs, and returns point forecasts with calibrated prediction intervals. Includes a preflight system checker script that MUST be run before first use to verify the machine can load the model. For classical statistical time series models (ARIMA, SARIMAX, VAR) use statsmodels; for time series classification/clustering use aeon.
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[omh] CRM pipeline or sales forecast to review: turn a supplied CRM export or pipeline snapshot into an evidence-bound pipeline health, forecast, and follow-up review. Aliases: pipeline-review, forecast-review, deal-review. Use when the user says: sales-pipeline-review, sales pipeline review, pipeline review, pipeline health, pipeline coverage, deal review, deal health, sales forecast review.
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Runs the planning cycle — annual budget, rolling forecast, consolidation of business unit inputs, and the variance analysis that explains actuals against plan. Use this to build or challenge a budget, run a forecast cycle, consolidate departmental submissions, explain why results diverged from plan, or improve forecast accuracy.
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Build a short-term (13-week) cash flow forecast to see if you can cover what's due. Use when asked to build a cash flow forecast, a 13-week cash flow, a cash projection, or to plan around a cash crunch. Produces a week-by-week forecast structure — opening cash, expected inflows, scheduled outflows, net movement, and closing/low-point — with the formulas and a worked example, plus the levers if cash goes tight. Not financial advice.
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Repository operating skill for using Flow Forecast's flood_forecast package for time-series forecasting, data preparation, training, inference, evaluation, and hydrology-oriented advanced models.
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Zero-shot univariate time series forecasting using the Reverso foundation model (NumPy/Numba CPU-only inference). Activate when users provide time series data and request forecasts, predictions, or extrapolations. Supports Reverso Small (550K params). Triggers on "forecast", "predict", "time series", "Reverso", or when tabular data with a temporal dimension needs future-value estimation.
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Survey existing forecasting code or models in a codebase — find gaps, stale models, and missing validation. Use when asked "what forecasting models do we have", "audit our forecasts", or "find stale models".
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Marketing budget planning and forecasting — channel allocation, CAC targets, ROI projections, and spend optimization. Use when "marketing budget", "budget planning", "channel allocation", "marketing spend", "CAC forecast", "budget forecast", "how much should I spend", "allocate budget", or any request to plan, forecast, or optimize marketing spend.
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Forecast infrastructure and application metrics using Prophet or statsmodels for capacity planning, cost optimization, and proactive scaling. Visualize predictions in Grafana and set up alerts for projected resource exhaustion. Use when forecasting infrastructure capacity needs for CPU, memory, or disk, planning hardware procurement for next quarter, predicting cost trends to optimize cloud spending, or setting up proactive scaling policies based on predicted load.
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"Build ARIMA models for time series forecasting with trend and seasonality decomposition. Use this skill when the user needs to forecast future values from historical sequential data, test for stationarity, or select ARIMA parameters — even if they say 'time series forecast', 'predict next month sales', or 'ARIMA model'.".
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Revenue Intelligence setup: activating the RI app and its CRM Analytics assets, Einstein deal insights, the opportunity-change waterfall, and forecast-accuracy analytics for sales leaders. NOT for configuring the Pipeline Inspection view, its metrics and review cadence - use admin/pipeline-review-design. NOT for forecast types, categories, rollups and quotas - use admin/collaborative-forecasts.
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Look up current weather and forecasts by city, region, airport code, or coordinates. Get concise summaries of temperature, feels-like temperature, rainfall, humidity, and wind for everyday outings and travel planning.
Fit regression and time series models in Python, interpret coefficients, compare alternatives, and check model assumptions. Supports statistical diagnostics and forecasting, with confidence intervals and validation steps to assess uncertainty and predictive performance.
Check current weather, today's outlook, or a full forecast for a city or airport code. Retrieve temperature, humidity, and wind information through free weather services without setting up an API key.
Complete an existing financial model template by entering historical data and forecast assumptions, then linking the income statement, balance sheet, and cash flow statement with formulas. Check statement balances, cash consistency, and scenario behavior as each section is completed.