learner

Capture conversation learnings into structured, searchable knowledge artifacts.

Updated Feb 14, 2026
One-click install
npx skills add https://github.com/shaun0927/codex-superskills --skill learner-shaun0927
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: learner
Source: https://github.com/shaun0927/codex-superskills/tree/main/skills/learner
Command: npx skills add https://github.com/shaun0927/codex-superskills --skill learner-shaun0927

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Extracting and preserving valuable reasoning and decision-making insights from conversations can be time-consuming and error-prone. This skill provides a principled way to capture those learnings for reuse across projects.

Core Features & Use Cases

  • Insight capture: summarize and store key takeaways, rationale, and next steps from a dialogue.
  • Knowledge reuse: apply saved learnings to new problems without re-deriving from scratch.
  • Use Case: after a complex design review, save the core decision points to guide future iterations.

Quick Start

Summarize the latest conversation into a reusable learning artifact and save it for future tasks.

Frequently Asked Questions about learner

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

FAQPage Schema
How do I capture insights and decisions from conversations for knowledge reuse?▼

Capturing insights from conversations involves summarizing key takeaways, rationale, and next steps into a structured knowledge artifact. This preserves decision-making context for reuse across future projects and tasks.

What is the best way to save learnings from a design review discussion?▼

Saving learnings from a design review involves extracting core decision points and summaries, linking to the source conversation, and storing them in a structured format to guide future iterations without re-deriving from scratch.

Can I store conversation summaries in a structured and searchable format?▼

Yes, conversation summaries can be stored in a structured, searchable format. This enables quick retrieval of rationale and context, allowing you to apply saved learnings to new problems without re-deriving from scratch.

Does capturing knowledge from conversations require any external dependencies?▼

No, capturing knowledge from conversations requires no external dependencies. The skill operates independently to codify learnings, ensuring you can extract and store insights without integrating additional frameworks or libraries.

Why should I codify learnings from discussions into reusable knowledge artifacts?▼

You should codify learnings into reusable knowledge artifacts to prevent time-consuming and error-prone manual extraction. It preserves valuable reasoning and decision-making context for application across different domains.