langchain-ai/remember

Review our conversation and capture valuable knowledge. Focus especially on best practices we discussed or discovered—these are the most important things to preserve.

Step 1: Identify Best Practices and Key Learnings

Scan the conversation for:

Best Practices (highest priority)

• Patterns that worked well - approaches, techniques, or solutions we found effective
• Anti-patterns to avoid - mistakes, gotchas, or approaches that caused problems
• Quality standards - criteria we established for good code, documentation, or processes
• Decision rationale - why we chose one approach over another

Other Valuable Knowledge

• Coding conventions and style preferences
• Project architecture decisions
• Workflows and processes we developed
• Tools, libraries, or techniques worth remembering
• Feedback I gave about your behavior or outputs

Step 2: Decide Where to Store Each Learning

For each best practice or learning, choose the right destination:

-> Memory (AGENTS.md) for preferences and guidelines

Use memory when the knowledge is:

• A preference or guideline (not a multi-step process)
• Something to always keep in mind
• A simple rule or pattern

Global (~/.deepagents/agent/AGENTS.md): Universal preferences across all projects Project (.deepagents/AGENTS.md): Project-specific conventions and decisions

-> Skill for reusable workflows and methodologies

Create a skill when we developed:

• A multi-step process worth reusing
• A methodology for a specific type of task
• A workflow with best practices baked in
• A procedure that should be followed consistently

Skills are more powerful than memory entries because they can encode how to do something well, not just what to remember.

Step 3: Create Skills for Significant Best Practices

If we established best practices around a workflow or process, capture them in a skill.

Example: If we discussed best practices for code review, create a code-review skill that encodes those practices into a reusable workflow.

Skill Location

~/.deepagents/agent/skills/<skill-name>/SKILL.md

Skill Structure

skill-name/
├── SKILL.md          (required - main instructions with best practices)
├── scripts/          (optional - executable code)
├── references/       (optional - detailed documentation)
└── assets/           (optional - templates, examples)

SKILL.md Format

---
name: skill-name
description: "What this skill does AND when to use it. Include triggers like 'when the user asks to X' or 'when working with Y'. This description determines when the skill activates."
---

# Skill Name

## Overview
Brief explanation of what this skill accomplishes.

## Best Practices
Capture the key best practices upfront:
- Best practice 1: explanation
- Best practice 2: explanation

## Process
Step-by-step instructions (imperative form):
1. First, do X
2. Then, do Y
3. Finally, do Z

## Common Pitfalls
- Pitfall to avoid and why
- Another anti-pattern we discovered

Key Principles

1. Encode best practices prominently - Put them near the top so they guide the entire workflow
2. Concise is key - Only include non-obvious knowledge. Every paragraph should justify its token cost.
3. Clear triggers - The description determines when the skill activates. Be specific.
4. Imperative form - Write as commands: "Create a file" not "You should create a file"
5. Include anti-patterns - What NOT to do is often as valuable as what to do

Step 4: Update Memory for Simpler Learnings

For preferences, guidelines, and simple rules that don't warrant a full skill:

## Best Practices
- When doing X, always Y because Z
- Avoid A because it leads to B

Use edit_file to update existing files or write_file to create new ones.

Step 5: Summarize Changes

List what you captured and where you stored it:

• Skills created (with key best practices encoded)
• Memory entries added (with location)