agent-memory

Use this skill when the user asks to save, remember, recall, or organize memories. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check your notes', 'clean up memories'. Also use proactively when discovering valuable findings worth preserving.

23,219 stars

Best use case

agent-memory is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Use this skill when the user asks to save, remember, recall, or organize memories. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check your notes', 'clean up memories'. Also use proactively when discovering valuable findings worth preserving.

Teams using agent-memory should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/agent-memory/SKILL.md --create-dirs "https://raw.githubusercontent.com/yamadashy/repomix/main/.claude/skills/agent-memory/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/agent-memory/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How agent-memory Compares

Feature / Agentagent-memoryStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Use this skill when the user asks to save, remember, recall, or organize memories. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check your notes', 'clean up memories'. Also use proactively when discovering valuable findings worth preserving.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Agent Memory

A persistent memory space for storing knowledge that survives across conversations.

**Location:** `.claude/skills/agent-memory/memories/`

## Proactive Usage

Save memories when you discover something worth preserving:
- Research findings that took effort to uncover
- Non-obvious patterns or gotchas in the codebase
- Solutions to tricky problems
- Architectural decisions and their rationale
- In-progress work that may be resumed later

Check memories when starting related work:
- Before investigating a problem area
- When working on a feature you've touched before
- When resuming work after a conversation break

Organize memories when needed:
- Consolidate scattered memories on the same topic
- Remove outdated or superseded information
- Update status field when work completes, gets blocked, or is abandoned

## Folder Structure

When possible, organize memories into category folders. No predefined structure - create categories that make sense for the content.

Guidelines:
- Use kebab-case for folder and file names
- Consolidate or reorganize as the knowledge base evolves

Example:
```text
memories/
├── file-processing/
│   └── large-file-memory-issue.md
├── dependencies/
│   └── iconv-esm-problem.md
└── project-context/
    └── december-2025-work.md
```

This is just an example. Structure freely based on actual content.

## Frontmatter

All memories must include frontmatter with a `summary` field. The summary should be concise enough to determine whether to read the full content.

**Summary is the decision point**: Agents scan summaries via `rg "^summary:"` to decide which memories to read in full. Write summaries that contain enough context to make this decision - what the memory is about, the key problem or topic, and why it matters.

**Required:**
```yaml
---
summary: "1-2 line description of what this memory contains"
created: 2025-01-15  # YYYY-MM-DD format
---
```

**Optional:**
```yaml
---
summary: "Worker thread memory leak during large file processing - cause and solution"
created: 2025-01-15
updated: 2025-01-20
status: in-progress  # in-progress | resolved | blocked | abandoned
tags: [performance, worker, memory-leak]
related: [src/core/file/fileProcessor.ts]
---
```

## Search Workflow

Use summary-first approach to efficiently find relevant memories:

```bash
# 1. List categories
ls .claude/skills/agent-memory/memories/

# 2. View all summaries
rg "^summary:" .claude/skills/agent-memory/memories/ --no-ignore --hidden

# 3. Search summaries for keyword
rg "^summary:.*keyword" .claude/skills/agent-memory/memories/ --no-ignore --hidden -i

# 4. Search by tag
rg "^tags:.*keyword" .claude/skills/agent-memory/memories/ --no-ignore --hidden -i

# 5. Full-text search (when summary search isn't enough)
rg "keyword" .claude/skills/agent-memory/memories/ --no-ignore --hidden -i

# 6. Read specific memory file if relevant
```

**Note:** Memory files are gitignored, so use `--no-ignore` and `--hidden` flags with ripgrep.

## Operations

### Save

1. Determine appropriate category for the content
2. Check if existing category fits, or create new one
3. Write file with required frontmatter (use `date +%Y-%m-%d` for current date)

```bash
mkdir -p .claude/skills/agent-memory/memories/category-name/
# Note: Check if file exists before writing to avoid accidental overwrites
cat > .claude/skills/agent-memory/memories/category-name/filename.md << 'EOF'
---
summary: "Brief description of this memory"
created: 2025-01-15
---

# Title

Content here...
EOF
```

### Maintain

- **Update**: When information changes, update the content and add `updated` field to frontmatter
- **Delete**: Remove memories that are no longer relevant
  ```bash
  trash .claude/skills/agent-memory/memories/category-name/filename.md
  # Remove empty category folders
  rmdir .claude/skills/agent-memory/memories/category-name/ 2>/dev/null || true
  ```
- **Consolidate**: Merge related memories when they grow
- **Reorganize**: Move memories to better-fitting categories as the knowledge base evolves

## Guidelines

1. **Write for resumption**: Memories exist to resume work later. Capture all key points needed to continue without losing context - decisions made, reasons why, current state, and next steps.
2. **Write self-contained notes**: Include full context so the reader needs no prior knowledge to understand and act on the content
3. **Keep summaries decisive**: Reading the summary should tell you if you need the details
4. **Stay current**: Update or delete outdated information
5. **Be practical**: Save what's actually useful, not everything

## Content Reference

When writing detailed memories, consider including:
- **Context**: Goal, background, constraints
- **State**: What's done, in progress, or blocked
- **Details**: Key files, commands, code snippets
- **Next steps**: What to do next, open questions

Not all memories need all sections - use what's relevant.

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