harvest-memory

Extract key learnings and architectural discoveries into a knowledge graph via Memory MCP tools.

349|98|Updated Feb 1, 2018
One-click install
npx skills add https://github.com/shopsys/shopsys --skill harvest-memory
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: harvest-memory
Source: https://github.com/shopsys/shopsys/tree/main/.agents/skills/harvest-memory
Command: npx skills add https://github.com/shopsys/shopsys --skill harvest-memory

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill systematically extracts and stores key learnings, architectural discoveries, and future improvement ideas from a conversation session, ensuring valuable insights are not lost.

Core Features & Use Cases

  • Session Summarization: Identifies the session's objective, strategies, successes, and failures.
  • Knowledge Persistence: Leverages Memory MCP tools to store extracted information in a structured knowledge graph.
  • Architecture Documentation: Captures insights about the application's architecture and potential optimizations.
  • Use Case: After a complex debugging session, use this Skill to automatically record the root cause, the fix, and any new architectural patterns discovered about the 'StorefrontApp'.

Quick Start

Use the harvest-memory skill to extract key learnings from this conversation.

Frequently Asked Questions about harvest-memory

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

FAQPage Schema
How do I save architectural discoveries and learnings from a conversation session?

To save architectural discoveries and learnings from a conversation session, you can extract key insights and persist them into a knowledge graph. This process structures your session analysis into entities and relations for future reference.

What is the best way to persist session analysis for software projects?

The best way to persist session analysis for software projects is to use Memory MCP tools to create structured entities and link relations. This builds a knowledge graph that captures objectives, strategies, and failures.

How do I document a debugging session's root cause and fix in a knowledge graph?

You document a debugging session's root cause and fix in a knowledge graph by applying post-session analysis to extract key learnings. Memory MCP tools add atomic observations and link relations to store the findings.

Do I need Memory MCP tools to extract and store key learnings?

Yes, you need Memory MCP tools to extract and store key learnings because the process relies on structured entity creation, relation linking, and atomic observation addition via these specific tools to build the graph.

Can I capture future improvement ideas for my application architecture automatically?

You can capture future improvement ideas for your application architecture by running a post-session analysis skill. It identifies potential optimizations and stores them as structured entities within your project's knowledge graph.