retain-learning

Classify new learnings and store them in Hindsight's retain tool.

1|Updated Mar 3, 2026

Search Tags:#knowledge management #memory #classification #agent workflows #hindsight #retain

Ready to run

npx skills add https://github.com/AndreJorgeLopes/devflow --skill retain-learning

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: retain-learning
Source: https://github.com/AndreJorgeLopes/devflow/tree/main/skills/retain-learning
Command: npx skills add https://github.com/AndreJorgeLopes/devflow --skill retain-learning

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps prevent valuable decisions, discoveries, and hard-won lessons from being lost between AI agent sessions.

Core Features & Use Cases

Learning capture: Converts a user-provided note into a structured memory when you don’t already have a full write-up.
Automatic classification: Tags the learning as a Mental Model, Hard Rule, Gotcha, Decision, Technique, or Discovery for better retrieval.
Hindsight retention: Stores the structured payload into Hindsight’s long-term memory using the Hindsight retain tool.

Quick Start

Use retain-learning to store a specific lesson for future sessions by telling your agent what you learned and including any relevant context or rationale.

Frequently Asked Questions about retain-learning

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

FAQPage Schema

How do I retain learning insights for future AI agent sessions?▼

To retain learning insights for future AI agent sessions, you capture the discovery or decision rationale and store it as a structured memory payload using a long-term memory tool. This prevents valuable decisions from being lost between sessions.

What is the best way to classify agent memory for better retrieval?▼

The best way to classify agent memory for better retrieval is to automatically tag the learning payload as a Mental Model, Hard Rule, Gotcha, Decision, Technique, or Discovery. This categorization structures the data for efficient future recall.

Can I preserve decision rationale and hard rules between agent workflows?▼

Yes, you can preserve decision rationale and hard rules between agent workflows by converting user-provided notes into a structured memory payload. This ensures hard-won lessons and specific gotchas are stored for later reuse.

How do you structure a memory payload from a raw note?▼

To structure a memory payload from a raw note, you parse the input arguments, classify the specific learning into a defined category, and invoke a memory retention tool to store the structured payload for future recall.

When do I need to store agent memory in Hindsight?▼

You need to store agent memory in Hindsight when you have a discovery, hard rule, decision rationale, technique, mental model, or gotcha to preserve. This is required to prevent valuable insights from being lost between AI agent sessions.