session-learnings

Generate investigation-log.md, README.md, chat-transcript.md, and Marp deck artifacts from AI coding sessions.

1|Updated Feb 10, 2026
One-click install
npx skills add https://github.com/ktundwal/session-learnings --skill session-learnings
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: session-learnings
Source: https://github.com/ktundwal/session-learnings/tree/main/session-learnings
Command: npx skills add https://github.com/ktundwal/session-learnings --skill session-learnings

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Capture learnings from AI coding sessions and turn them into durable, portable artifacts that survive beyond the chat.

Core Features & Use Cases

  • Generates an investigation-log.md documenting decisions, dead ends, and rationale
  • Creates a README.md summary, chat-transcript.md, and a Marp deck (deck.md / deck.pptx / deck.html)
  • Updates MEMORY.md with new learnings to feed auto-memory systems

Quick Start

Run the /session-learnings [topic-name] command at the end of a productive session to begin collecting artifacts.

Frequently Asked Questions about session-learnings

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

FAQPage Schema
How do I capture AI coding session learnings as durable documentation artifacts?▼

Capture session learnings by generating portable artifacts like investigation-log.md and chat-transcript.md that preserve coding decisions and breakthroughs beyond the chat context.

What's the best way to document coding session decisions and dead ends for future reference?▼

Documenting session decisions is best handled by generating an investigation-log.md that records rationale, dead ends, and breakthroughs alongside a chat-transcript.md for full context.

How do I generate a Marp deck from a coding session transcript?▼

Generate a Marp deck by running an end-of-session workflow that extracts context and exports deck.md, deck.pptx, and deck.html files summarizing the coding session.

Does this session capture workflow require any external dependencies or components?▼

No external dependencies or components are required. The session capture workflow operates independently to extract context, generate artifacts, perform optional cross-model review, and update memory files.

How do I update MEMORY.md with new learnings from an investigation log?▼

Update MEMORY.md by running an end-of-session workflow that integrates new learnings from the generated investigation log directly into the memory file to feed auto-memory systems.

When should I use an automated session capture workflow instead of manual note-taking?▼

Use automated session capture at the end of productive AI coding sessions when you need deterministic, searchable documentation artifacts and memory integration rather than relying on manual notes.