agent-memory

# 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- Remove outdated or superseded information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