meta-cognitive-reasoning

Enforce evidence-first reasoning with multiple hypotheses and self-correction protocols.

4|Updated Dec 23, 2025

Search Tags:#meta-cognition #reasoning #evidence #critical-thinking #hypotheses #cognitive-bias

Ready to run

npx skills add https://github.com/89jobrien/steve --skill meta-cognitive-reasoning

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: meta-cognitive-reasoning
Source: https://github.com/89jobrien/steve/tree/main/steve/skills/meta-cognitive-reasoning
Command: npx skills add https://github.com/89jobrien/steve --skill meta-cognitive-reasoning

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides disciplined reasoning frameworks to avoid cognitive failures and enforce evidence-based conclusions.

Core Features & Use Cases

Evidence-Based Reasoning: Show data before interpretation
Multiple Hypotheses: Generate competing hypotheses
Temporal Knowledge Validation: Consider knowledge cutoff
Self-Correction & Traceability: Transparent correction path

Quick Start

Use structured reasoning protocol before giving conclusions.

Frequently Asked Questions about meta-cognitive-reasoning

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

FAQPage Schema

How do I avoid cognitive bias when analyzing code or making decisions?▼

Cognitive bias clouds judgment during analysis and decision-making. This Skill provides disciplined reasoning frameworks that enforce evidence-first interpretation, generate multiple competing hypotheses, and apply self-correction protocols to prevent premature conclusions and ensure conclusions rest on data, not assumption.

What's the best way to structure reasoning during code reviews and architectural assessments?▼

Structured reasoning during reviews prevents overlooking critical issues. Use evidence-based reasoning frameworks to separate observation from interpretation, document temporal knowledge validity, and systematically trace your correction path so conclusions remain transparent and defensible.

How do I ensure my conclusions are evidence-based rather than assumption-driven?▼

Evidence-based conclusions require showing data before interpretation and validating knowledge currency against your information cutoff. This Skill enforces evidence-first discipline, requiring you to present supporting data and consider temporal constraints before drawing conclusions during unfamiliar analysis or pattern recognition.

Can I use structured reasoning frameworks when debugging or analyzing unfamiliar patterns?▼

Yes. Structured reasoning applies across code reviews, architectural assessments, documentation analysis, and unfamiliar patterns. The frameworks enforce systematic completion discipline and generate multiple hypotheses, helping you identify root causes and patterns when working outside familiar territory.

Why does reasoning fail during critical analysis and how do I prevent it?▼

Reasoning fails when cognitive biases go unchecked and conclusions outpace evidence. This Skill prevents failures by enforcing evidence-first interpretation, temporal knowledge awareness, transparent self-correction, and systematic discipline—building accountability into your analytical process across reviews and decision-making.

What should I do before drawing conclusions from analysis or debugging work?▼

Apply disciplined meta-cognitive reasoning frameworks before concluding. Review evidence completeness, validate knowledge currency, consider competing hypotheses, and document your correction path to ensure conclusions are evidence-based and temporally grounded rather than driven by cognitive shortcuts.