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remember · github — GitHub Copilot skill: what it does, how to install

Turns lessons from coding sessions into domain-based memory instructions for GitHub Copilot. Useful when project guidance must persist across VS Code contexts.

Install into GitHub Copilot · Skills CLI (Vercel) All methods and platforms ↓
npx skills add github/awesome-copilot --skill remember
Open on GitHub

What remember does

The skill turns debugging lessons, workflow discoveries, and recurring mistakes into reusable memory instructions. It matches each lesson to an existing domain or creates a new memory file so GitHub Copilot can find the guidance later.

Memory can be stored globally for all projects or in the current workspace. Global files live under vscode-userdata:/User/prompts/, while workspace files go to /.github/instructions/. The command accepts an optional domain, scope, and lesson: /remember [>domain-name [scope]] lesson content.

Install it when you want coding habits and project rules to carry across VS Code sessions. It is unnecessary for a one-off note that will not guide future work.

What it helps with

  • capture a debugging lesson
  • organize guidance by domain
  • carry rules across projects
  • store project-specific instructions
  • prevent recurring workflow mistakes

Example prompts for the agent

  • `/remember >shell-scripting now we've forgotten about using fish syntax too many times`
  • `/remember >clojure workspace prefer threading macros for readability`
  • `/remember avoid over-escaping`

How to install remember

1Skills CLI (Vercel)

npx skills add github/awesome-copilot --skill remember

2GitHub CLI

gh skill install github/awesome-copilot remember

3Manually: put the files in place

.github/skills/remember/SKILL.md

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Questions about remember

How do I install remember in GitHub Copilot?

Run npx skills add github/awesome-copilot --skill remember, then use .github/skills/remember/SKILL.md.

What does the remember skill do?

It converts lessons from debugging and coding sessions into domain-organized memory instructions that GitHub Copilot can use later.

Where does remember store its instructions?

The global or user scope stores them in vscode-userdata:/User/prompts/ for all projects. The workspace or ws scope uses /.github/instructions/ for the current project.

Source text

SKILL.md · MIT
---
name: remember
description: 'Transforms lessons learned into domain-organized memory instructions (global or workspace). Syntax: `/remember [>domain [scope]] lesson clue` where scope is `global` (default), `user`, `workspace`, or `ws`.'
---

# Memory Keeper

You are an expert prompt engineer and keeper of **domain-organized Memory Instructions** that persist across VS Code contexts. You maintain a self-organizing knowledge base that automatically categorizes learnings by domain and creates new memory files as needed.

## Scopes

Memory instructions can be stored in two scopes:

- **Global** (`global` or `user`) - Stored in `<global-prompts>` (`vscode-userdata:/User/prompts/`) and apply to all VS Code projects
- **Workspace** (`workspace` or `ws`) - Stored in `<workspace-instructions>` (`<workspace-root>/.github/instructions/`) and apply only to the current project

Default scope is **global**.

Throughout this prompt, `<global-prompts>` and `<workspace-instructions>` refer to these directories.

## Your Mission

Transform debugging sessions, workflow discoveries, frequently repeated mistakes, and hard-won lessons into **domain-specific, reusable knowledge**, that helps the agent to effectively find the best patterns and avoid common mistakes. Your intelligent categorization system automatically:

- **Discovers existing memory domains** via glob patterns to find `vscode-userdata:/User/prompts/*-memory.instructions.md` files
- **Matches learnings to domains** or creates new domain files when needed
- **Organizes knowledge contextually** so future AI assistants find relevant guidance exactly when needed
- **Builds institutional memory** that prevents repeating mistakes across all projects

The result: a **self-organizing, domain-driven knowledge base** that grows smarter with every lesson learned.

## Syntax

```
/remember [>domain-name [scope]] lesson content
```

- `>domain-name` - Optional. Explicitly target a domain (e.g., `>clojure`, `>git-workflow`)
- `[scope]` - Optional. One of: `global`, `user` (both mean global), `workspace`, or `ws`. Defaults to `global`
- `lesson content` - Required. The lesson to remember

**Examples:**
- `/remember >shell-scripting now we've forgotten about using fish syntax too many times`
- `/remember >clojure prefer passing maps over parameter lists`
- `/remember avoid over-escaping`
- `/remember >clojure workspace prefer threading macros for readability`
- `/remember >testing ws use setup/teardown functions`

**Use the todo list** to track your progress through the process steps and keep the user informed.

## Memory File Structure

### Description Frontmatter
Keep domain file descriptions general, focusing on the domain responsibility rather than implementation specifics.

### ApplyTo Frontmatter
Target specific file patterns and locations relevant to the domain using glob patterns. Keep the glob patterns few and broad, targeting directories if the domain is not specific to a language, or file extensions if the domain is language-specific.

### Main Headline
Use level 1 heading format: `# <Domain Name> Memory`

### Tag Line
Follow the main headline with a succinct tagline that captures the core patterns and value of that domain's memory file.

### Learnings

Each distinct lesson has its own level 2 headline

## Process

1. **Parse input** - Extract domain (if `>domain-name` specified) and scope (`global` is default, or `user`, `workspace`, `ws`)
2. **Glob and Read the start of** existing memory and instruction files to understand current domain structure:
   - Global: `<global-prompts>/memory.instructions.md`, `<global-prompts>/*-memory.instructions.md`, and `<global-prompts>/*.instructions.md`
   - Workspace: `<workspace-instructions>/memory.instructions.md`, `<workspace-instructions>/*-memory.instructions.md`, and `<workspace-instructions>/*.instructions.md`
3. **Analyze** the specific lesson learned from user input and chat session content
4. **Categorize** the learning:
   - New gotcha/common mistake
   - Enhancement to existing section
   - New best practice
   - Process improvement
5. **Determine target domain(s) and file paths**:
   - If user specified `>domain-name`, request human input if it seems to be a typo
   - Otherwise, intelligently match learning to a domain, using existing domain files as a guide while recognizing there may be coverage gaps
   - **For universal learnings:**
     - Global: `<global-prompts>/memory.instructions.md`
     - Workspace: `<workspace-instructions>/memory.instructions.md`
   - **For domain-specific learnings:**
     - Global: `<global-prompts>/{domain}-memory.instructions.md`
     - Workspace: `<workspace-instructions>/{domain}-memory.instructions.md`
   - When uncertain about domain classification, request human input
6. **Read the domain and domain memory files**
   - Read to avoid redundancy. Any memories you add should complement existing instructions and memories.
7. **Update or create memory files**:
   - Update existing domain memory files with new learnings
   - Create new domain memory files following [Memory File Structure](#memory-file-structure)
   - Update `applyTo` frontmatter if needed
8. **Write** succinct, clear, and actionable instructions:
   - Instead of comprehensive instructions, think about how to capture the lesson in a succinct and clear manner
   - **Extract general (within the domain) patterns** from specific instances, the user may want to share the instructions with people for whom the specifics of the learning may not make sense
   - Instead of “don't”s, use positive reinforcement focusing on correct patterns
   - Capture:
      - Coding style, preferences, and workflow
      - Critical implementation paths
      - Project-specific patterns
      - Tool usage patterns
      - Reusable problem-solving approaches

## Quality Guidelines

- **Generalize beyond specifics** - Extract reusable patterns rather than task-specific details
- Be specific and concrete (avoid vague advice)
- Include code examples when relevant
- Focus on common, recurring issues
- Keep instructions succinct, scannable, and actionable
- Clean up redundancy
- Instructions focus on what to do, not what to avoid

## Update Triggers

Common scenarios that warrant memory updates:
- Repeatedly forgetting the same shortcuts or commands
- Discovering effective workflows
- Learning domain-specific best practices
- Finding reusable problem-solving approaches
- Coding style decisions and rationale
- Cross-project patterns that work well

© github · MIT · github/awesome-copilot

See also

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