rrr

Create structured retrospectives for coding and research sessions.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/thiansit/LuPang --skill rrr-thiansit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rrr
Source: https://github.com/thiansit/LuPang/tree/main/.claude/skills/rrr
Command: npx skills add https://github.com/thiansit/LuPang --skill rrr-thiansit

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Capture end-of-session context, timeline, and lessons so work sessions do not lose momentum or the learnings created during coding, research, or design work. The skill automates assembly of a concise retrospective, an AI diary, and a lesson file while weaving optional pulse context and git metadata into a single narrative for future reference.

Core Features & Use Cases

  • Quick Retro: Generate a short, practical retrospective and commit it to the project's memory store.
  • Full Template: Produce a detailed session report with timeline, files modified, architecture notes, honest feedback, and metrics for in-depth reflection.
  • Timeline Reconstruction: Use session logs and exported .jsonl traces to rebuild session timelines and map activities to commits.
  • Deep Analysis: Optionally run a five-agent deep mode to parallelize git analysis, file change summaries, pattern extraction, and Oracle memory searches.
  • Persistent Learning: Save lessons to the local Oracle memory and optionally sync insights back to the Oracle using the oracle_learn call.

Quick Start

Run /rrr to create a concise retrospective and save it to psi/memory/retrospectives while also writing a lesson file to psi/memory/learnings and syncing insights to the Oracle.

Frequently Asked Questions about rrr

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

FAQPage Schema
How do I create a coding session retrospective with git metadata?▼

To create a coding session retrospective, run a quick retro command to capture timeline, file changes, and lessons learned, then commit the report to your project's local psi/memory paths.

What is an AI diary entry for research sessions?▼

An AI diary entry for research sessions is a structured narrative that captures context, pulse data, and lessons learned, assembled automatically to prevent work momentum loss.

How do I reconstruct a session timeline from exported jsonl traces?▼

Reconstruct a session timeline by importing exported .jsonl traces and session logs to rebuild chronological activities and map them directly to git commits.

Can I sync lessons learned directly to local Oracle memory?▼

Yes, you can sync lessons learned directly to local Oracle memory using the optional oracle_learn synchronization call while operating in GMT+7 time.

When do I need a deep multi-agent analysis for session retrospectives?▼

You need deep multi-agent analysis for complex sessions requiring parallel git analysis, file change summaries, pattern extraction, and Oracle memory searches.

Does retrospective generation work without external dependencies?▼

Yes, retrospective generation works without external dependencies, saving structured files locally to psi/memory/retrospectives and psi/memory/learnings.