retrospect

Capture reusable lessons from AI coding sessions into a project knowledge registry.

Updated Jun 22, 2026
One-click install
npx skills add https://github.com/Elad73/agentic-base-layer --skill retrospect-elad73
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: retrospect
Source: https://github.com/Elad73/agentic-base-layer/tree/main/global/skills/retrospect
Command: npx skills add https://github.com/Elad73/agentic-base-layer --skill retrospect-elad73

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Captures important lessons from a completed work session so future sessions do not repeat the same mistakes or miss the same useful patterns.

Core Features & Use Cases

  • Session analysis: Reviews what was accomplished, what worked, what failed, and why.
  • Knowledge extraction: Classifies durable insights as patterns, pitfalls, architecture decisions, performance findings, or security notes.
  • Registry writing: Appends structured entries to the project knowledge registry with IDs, tags, context, learning, application guidance, and measurable impact.
  • Use case: After fixing a tricky bug or making a non-obvious design decision, record the lesson so the next engineer can reuse it immediately.

Quick Start

Ask retrospect to review the conversation, extract the most valuable durable lessons, and append them to the project knowledge registry.

Frequently Asked Questions about retrospect

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

FAQPage Schema
How do I capture lessons learned from an AI coding session into a project knowledge registry?

Capture session lessons by analyzing the completed work to extract durable insights, then append structured entries with IDs, tags, context, and application guidance into the project knowledge registry. This records non-obvious outcomes from bug fixes or architectural decisions for future reuse.

What is the best way to document engineering notes after a complex bug fix?

The best way to document engineering notes is to classify the durable insights as patterns, pitfalls, or architecture decisions. Generate structured, category-tagged entries with concrete application guidance and falsifiable impact metrics, then write them to the registry.

Can I record architectural decisions and performance findings for future sessions to reuse?

Yes, you can record architectural decisions and performance findings by extracting these durable insights from the session. The process classifies them and appends structured entries with sequential IDs and context to the project knowledge registry for future sessions.

How does a session review extract knowledge from rework or non-obvious outcomes?

Session review extracts knowledge by examining what was accomplished, what worked, what failed, and why. It identifies durable insights from rework or non-obvious outcomes, then writes them as structured entries with falsifiable impact metrics to the registry.

Does writing lessons learned to a knowledge registry require any external dependencies?

No external dependencies are required to write lessons learned to the knowledge registry. The process operates independently to analyze the session, extract insights, and append structured entries directly to the project registry file.

When should I not use a retrospective for knowledge capture?

You should not use a retrospective for obvious or routine changes that lack non-obvious outcomes. It is designed for post-session reviews after complex bug fixes, architectural decisions, or rework where durable insights and measurable impacts need to be captured.