smithery.ai

forecast-modeling

Use when designing, tuning, or auditing revenue forecast models.

First seen Apr 10, 2026

Installation

$ npx skills add https://smithery.ai

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,320 B
  • docs SUMMARY.md 89 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Forecast Modeling System Skill

When to Use

  • Launching new forecasting cadences or revisiting methodology.
  • Running scenario planning ahead of board meetings or budget cycles.
  • Auditing deviations between forecast, pipeline, and actuals.

Framework

  1. Method Selection – pick bottom-up CRM, top-down macro, cohort, or blended models and document assumptions.
  2. Driver Mapping – define win rates, velocity, expansion, churn, pricing, and seasonality inputs.
  3. Scenario Logic – establish base/upside/downside cases with tunable levers for sensitivity analysis.
  4. Model Governance – list data sources, refresh cadence, validation checks, and ownership.
  5. Output Packaging – standardize tables, charts, and narrative prompts for exec review.

Templates

  • Driver tree diagram connecting levers to KPIs.
  • Scenario sheet (assumption → base/upside/downside values).
  • Model QA checklist (data freshness, formula audits, version history).

Tips

  • Keep raw inputs + assumptions in version control for auditability.
  • Pair with variance-analysis skill to recalibrate after each cycle.
  • Automate sensitivity runs to answer "what-if" questions during reviews.