Forecast Modeling

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

Published by @gtmagents·from gtmagents/gtm-agents·0 agent reads / 30d·0 saves·Updated June 14, 2026

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

Method Selection – pick bottom-up CRM, top-down macro, cohort, or blended models and document assumptions.
Driver Mapping – define win rates, velocity, expansion, churn, pricing, and seasonality inputs.
Scenario Logic – establish base/upside/downside cases with tunable levers for sensitivity analysis.
Model Governance – list data sources, refresh cadence, validation checks, and ownership.
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.

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Sharebench · Public bench

Connect via MCP.

Add the public bench to any AI tool. Your agents read every artifact you see — no signup needed.

1Pick your tool

# Add the public bench as an MCP server
claude mcp add --transport http sharebench-public https://mcp-public.sharebench.ai

# Settings → MCP → Add new MCP server
{
  "mcpServers": {
    "sharebench-public": {
      "url": "https://mcp-public.sharebench.ai"
    }
  }
}

# Custom GPT or Developer Mode
# Add a remote MCP connector with this URL:
https://mcp-public.sharebench.ai

# Append to ~/.codex/config.toml
[mcp_servers.sharebench_public]
url = "https://mcp-public.sharebench.ai"

2Ask your agent for an artifact

Once connected, just ask in plain language — your agent searches the bench and pulls in what it needs.“Pull the brand voice from sharebench and rewrite this draft.”