pipeline-ground-truth

Generate categorized assumptions from BRIEF.json into GROUND-TRUTH.json.

4|Updated Apr 9, 2026
One-click install
npx skills add https://github.com/danielgap/openclaw-planitor --skill pipeline-ground-truth
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pipeline-ground-truth
Source: https://github.com/danielgap/openclaw-planitor/tree/main/skills/pipeline-ground-truth
Command: npx skills add https://github.com/danielgap/openclaw-planitor --skill pipeline-ground-truth

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Ground Truth phase documents base assumptions for a business plan, organizing them into clear categories (market, product/service, costs, sales, and real data) to support validation and planning.

Core Features & Use Cases

  • Generate five categorized assumption blocks from BRIEF.json: market, product/service, costs, sales, and real data.
  • Include mandatory local seasonality data and a dedicated competition insights section.
  • Output: GROUND-TRUTH.json at projects/{proyecto}/v{n}/ with per-assumption value, source, and status.

Quick Start

Read the BRIEF.json for a project and generate a GROUND-TRUTH.json containing categorized assumptions at the specified path.

Frequently Asked Questions about pipeline-ground-truth

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I document ground-truth assumptions for business planning?

Ground-truth assumptions are documented by generating a categorized JSON file from a project brief. This process organizes assumptions into market, product, costs, sales, and real data blocks, capturing per-assumption value, source, and status for validation.

Can I generate market size and competitor analysis assumptions from BRIEF.json?

Yes, you can generate market size and competitor analysis assumptions directly from BRIEF.json. The process creates categorized blocks that include a dedicated competition insights section and mandatory local seasonality data for business planning.

What is the best way to structure categorized assumptions for market and sales data?

The best way to structure categorized assumptions is using a JSON format divided into five blocks: market, product/service, costs, sales, and real data. Each assumption entry must include its value, source, and validation status.

Does the ground-truth generation process require local seasonality data?

Yes, the ground-truth generation process requires mandatory local seasonality data gathering. This data is integrated into the categorized assumptions document alongside market, product, costs, and sales blocks to support accurate planning.

How do I output categorized assumptions to a specific project version path?

You output categorized assumptions by generating a GROUND-TRUTH.json file at the projects/{proyecto}/v{n} directory path. This file contains the structured assumptions derived from the input BRIEF.json for that specific project version.