meta

Name: meta
Availability: InStock
Author: Atris

Provides metacognitive guidance for AI agents to improve self-awareness and decision-making through checkable workflows.

Updated Feb 16, 2026

Search Tags:#workflow #planning #decision making #ai agent #metacognition #self-correction

Ready to run

npx skills add https://github.com/atrislabs/atris-plugins --skill meta-atrislabs

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: meta
Source: https://github.com/atrislabs/atris-plugins/tree/main/plugins/atris-workspace/skills/meta
Command: npx skills add https://github.com/atrislabs/atris-plugins --skill meta-atrislabs

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps AI agents improve their decision-making, self-correction, and overall effectiveness by providing a framework for metacognition and structured thinking.

Core Features & Use Cases

Self-Assessment: Guides agents to check their approach before and during task execution.
Contextual Awareness: Ensures agents leverage available information like maps, journals, and past lessons.
Pacing and Correction: Provides signals for adjusting task speed and triggers for self-correction.
Use Case: When an agent is about to start a complex coding task, it can activate the meta skill to ensure it first reviews the project map, checks its journal for relevant context, and plans its approach before writing any code.

Quick Start

Use the meta skill to orient yourself before starting the new project.

Frequently Asked Questions about meta

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

FAQPage Schema

How do I add metacognition to my AI agent for better decision making?▼

Metacognition guides AI agents to improve decision-making and self-correction by enforcing a structured loop of orient, decide, act, check, and learn during task execution. It ensures agents review project maps and past lessons before acting.

What is the best way to prevent AI agents from rushing into complex coding tasks?▼

Preventing rushed execution requires pace control and self-assessment signals. A metacognitive framework triggers agents to check their approach, review contextual journals, and plan thoroughly before writing any code.

How does an AI agent perform self-correction during workflow execution?▼

Self-correction during workflow execution relies on referencing project maps, journals, and past lessons. Agents follow a structured loop to check their context and adjust their actions, actively avoiding common anti-patterns.

When do I need structured planning and context checking for AI workflows?▼

You need structured planning when starting complex projects that require high self-awareness. Context checking ensures agents leverage available information like maps and journals, preventing errors before task execution begins.

Does metacognitive guidance work without external dependencies?▼

Yes, metacognitive guidance works without external dependencies. It operates as an internal framework using references to provide self-assessment, pacing signals, and self-correction mechanisms for AI agents.

Why does my AI agent repeat the same mistakes across different tasks?▼

Agents repeat mistakes without a structured learning loop. Metacognition solves this by enforcing a check and learn phase, ensuring past lessons and journals are referenced to trigger self-correction and avoid anti-patterns.