Forecast Confidence is a skill that takes deal-level CSV exports from CRM tools such as Salesforce, HubSpot, or custom spreadsheets and runs 10,000 Monte Carlo simulation iterations to produce probabilistic revenue projections. Rather than applying a flat close-probability multiplier to each deal, the skill models volatility across the full pipeline and returns statistical confidence intervals at the P50, P70, and P90 percentiles, giving sales teams a data-backed answer to whether they will hit a revenue target rather than a single weighted estimate.
The output includes a P50 median forecast, detailed confidence intervals, an ASCII distribution histogram that visualizes the revenue spread, and data-quality warnings when input data is incomplete. When stage conversion rates are missing from the CSV, the skill applies industry-standard stage defaults to maintain simulation integrity. The skill also supports what-if scenario analysis: changing close dates or deal amounts recalculates the quarterly floor and ceiling so teams can test the impact of slippage before it happens. Accuracy scoring evaluates individual rep performance against historical stage conversion deltas.
This skill is appropriate when a pipeline exists as a structured CSV and the goal is statistically grounded forecasting. It is not a live CRM integration and does not query a database directly; it requires a CSV export as its input. There are no environment variables to configure and no package installation steps.