mma-journal-record

Record team decisions and learnings into the persistent knowledge graph.

5|4|Updated Apr 9, 2026
One-click install
npx skills add https://github.com/zhixuan312/multi-model-agent --skill mma-journal-record
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mma-journal-record
Source: https://github.com/zhixuan312/multi-model-agent/tree/main/packages/server/src/skills/mma-journal-record
Command: npx skills add https://github.com/zhixuan312/multi-model-agent --skill mma-journal-record

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Captures and stores hard-won insights (decisions, design rationales, user behavior patterns, process learnings, research findings, or style conventions) into the team's persistent knowledge graph for cross-session reference.

Core Features & Use Cases

  • Records key outcomes: decisions made, rationale, and supporting context after a task or project milestone.
  • Builds a centralized knowledge graph that teammates can consult during planning and audits.
  • Supports future sessions by preserving context and avoiding rework.

Quick Start

Log a decision or learning to the team knowledge graph.

Frequently Asked Questions about mma-journal-record

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

FAQPage Schema
How do I record team decisions and design rationale into a knowledge graph?▼

You can record team decisions and design rationale into a knowledge graph by logging decisions, user behavior patterns, and process learnings into a persistent .mma journal store for cross-session reference.

What is the best way to preserve process learnings and observations after a retrospective?▼

The best way to preserve process learnings after a retrospective is to capture key outcomes and supporting context into a centralized knowledge graph, ensuring teammates can consult them during future planning and audits.

When do I need to log entries to a persistent knowledge graph?▼

You need to log entries to a persistent knowledge graph after a milestone, review, or retrospective to ensure decisions, design rationales, and style conventions are preserved for future sessions.

Does this approach support indexing research findings and style conventions for future sessions?▼

Yes, this approach supports indexing research findings and style conventions by writing team knowledge entries into the durable .mma journal store, which builds a centralized knowledge graph to prevent rework.

Can I avoid rework by building a centralized knowledge graph for cross-session reference?▼

Yes, you can avoid rework by building a centralized knowledge graph that captures hard-won insights and supporting context, allowing teammates to consult the preserved observations during future planning.