recipe-analysis

Generate Goose recipes for analyzing markdown, JSON, and CSV documents.

1|Updated Sep 17, 2025

Search Tags:#analysis #insight extraction #recipe #document transformation #saved data #report analysis

Ready to run

npx skills add https://github.com/mpazaryna/agentic-factory --skill recipe-analysis

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: recipe-analysis
Source: https://github.com/mpazaryna/agentic-factory/tree/main/platform/goose/skills/recipe-analysis
Command: npx skills add https://github.com/mpazaryna/agentic-factory --skill recipe-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

This Skill enables the analysis and transformation of pre-existing documents, such as reports, without needing to query live data sources, streamlining insights extraction from static files.

Core Features & Use Cases

Analyze Saved Reports: Process markdown, JSON, or CSV files to extract insights.
Transform Documents: Enrich existing files with new context or recommendations.
Extract Insights: Generate actionable recommendations from static data.
Use Case: Analyze a quarterly sales report (saved as a markdown file) to identify key trends and generate a summary of actionable recommendations for the next quarter.

Quick Start

Use the recipe-analysis skill to create a recipe for mill/spec/your-analysis-spec.md

Frequently Asked Questions about recipe-analysis

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

FAQPage Schema

How do I analyze and extract insights from saved markdown, JSON, or CSV reports?▼

To analyze saved reports, you can generate custom YAML recipes and shell script runners that extract key information and actionable insights from static markdown, JSON, and CSV files. This streamlines offline document analysis without querying live data sources.

Can I transform existing documents to add new context or recommendations?▼

Yes, you can transform documents by applying custom recipes to enrich existing static files with new context. This process extracts key information and generates actionable recommendations directly from your saved offline data.

What is the best way to automate deterministic workflows for offline document analysis?▼

The best way to automate deterministic workflows is by generating YAML recipes and shell script runners. This approach ensures consistent, repeatable processing and insight extraction from your saved static documents.

Does this recipe analysis approach work for static files without live data querying?▼

Yes, this approach is specifically designed for offline document analysis of static files. It processes pre-existing reports in markdown, JSON, and CSV formats to extract insights, completely distinct from live data querying.

How do I generate a recipe for a custom document analysis spec?▼

You can generate a recipe by pointing the analysis tool to your custom document spec file. It will read the spec, extract key information, and automatically generate the required YAML recipe and shell script runner.

Are there limitations when using generated recipes for static report analysis?▼

The main limitation is that this process is restricted to offline document analysis of pre-existing files. It cannot query live data sources, meaning all insights and transformations must be derived from static markdown, JSON, or CSV reports.