beo-compounding

Generate structured learnings from .beads artifacts and git history.

Updated Jun 2, 2026

Search Tags:#decisions #patterns #artifacts #learnings #feature-review #knowledge-store #compounding

Ready to run

npx skills add https://github.com/minhtri2710/skills --skill beo-compounding

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: beo-compounding
Source: https://github.com/minhtri2710/skills/tree/main/skills/beo/compounding
Command: npx skills add https://github.com/minhtri2710/skills --skill beo-compounding

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Capture learnings from completed feature work to improve future planning and execution, reducing repeated mistakes and enabling faster, smarter feature delivery.

Core Features & Use Cases

Orchestrates a multi-agent compounding workflow (Pattern Extractor, Decision Analyst, Failure Analyst) to surface reusable learnings.
Generates structured outputs to .beads/learnings/YYYYMMDD-slug.md and promotes critical items to .beads/critical-patterns.md.
Integrates with knowledge-store references to enable knowledge retention and retrieval across features.

Quick Start

Run compounding after feature review to generate learnings from artifacts and commit them to the learnings store.

Frequently Asked Questions about beo-compounding

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

FAQPage Schema

How do I capture learnings from completed features to avoid repeating mistakes?▼

To capture learnings from completed features, extract reusable patterns and decisions from .beads artifacts and git history, then generate structured outputs to .beads/learnings and update .beads/STATE.md to prevent repeated mistakes.

What is the best way to extract reusable patterns and decisions from project artifacts?▼

The best way to extract reusable patterns is using a multi-agent workflow with Pattern Extractor and Decision Analyst roles to analyze .beads artifacts and git history, generating structured learnings for future planning.

Can I promote critical patterns to a dedicated knowledge store for future features?▼

Yes, you can promote critical patterns to .beads/critical-patterns.md and integrate with optional knowledge-store references to retain and retrieve reusable learnings across future features.

When should I run a feature review compounding workflow?▼

Run a feature review compounding workflow immediately after completing a feature to gather artifacts, analyze failures, and commit structured learnings to the learnings store while context is fresh.

Does the learnings extraction process require external dependencies?▼

No external dependencies are required. The process gathers artifacts directly from local .beads artifacts and git history, using optional knowledge-store references to generate structured learnings.