metacog-reflect

Analyze memory streams to detect knowledge gaps and duplicate memories.

6|Updated Feb 26, 2026
One-click install
npx skills add https://github.com/Acosmi/CrabClaw --skill metacog-reflect
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: metacog-reflect
Source: https://github.com/Acosmi/CrabClaw/tree/main/docs/skills/tools/memory/metacog-reflect
Command: npx skills add https://github.com/Acosmi/CrabClaw --skill metacog-reflect

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze recent memory streams to identify patterns that indicate knowledge gaps and provide actionable insights for cognitive improvement.

Core Features & Use Cases

  • Reflection analysis of recent high-importance memories to extract insights.
  • Duplicate detection and consolidation of overlapping memories to reduce clutter.
  • Imagination phase generates forward-looking predictions and counterfactual scenarios using knowledge graphs.

Quick Start

Trigger the reflection workflow by sending memory.metacog.trigger with type reflection.

Frequently Asked Questions about metacog-reflect

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

FAQPage Schema
How do I identify knowledge gaps in long-running agent memory streams?

Memory deduplication consolidates overlapping memories to reduce clutter by analyzing recent memory streams and merging redundant data points. This process identifies patterns across large memory stores to streamline long-running agent memory management.

How does metacognitive reflection work for autonomous agents?

To trigger reflection analysis, you send a manual trigger with the type set to reflection. This initiates the workflow that analyzes recent high-importance memories to extract insights and identify knowledge gaps.

What is the best way to perform memory deduplication for large memory stores?

The best way to perform memory deduplication is through a reflection analysis that consolidates overlapping memories to reduce clutter. It processes large memory stores to extract insights and reveal knowledge gaps across long-running agents.

Can I generate forward-looking predictions using agent memory analysis?

Yes, you can generate forward-looking predictions and counterfactual scenarios using an imagination phase built on knowledge graphs during memory analysis. This metacognitive process extracts insights from recent memory streams to predict future states.

Does memory reflection support manual triggers and structured inputs?

Yes, memory reflection supports manual triggers and structured memory inputs to produce a concise reflection plus an audit trail. This setup meets functional requirements for a metacognitive reflector managing long-running agent memory.