agent-memory

norifumi3's avatarfrom norifumi3

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', 'stop here', 'pause this', 'record this', 'log this'. Also use proactively when discovering valuable findings worth preserving.

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[Memory and Context Management]

When & Why to Use This Skill

The Agent Memory skill empowers Claude with a persistent, structured knowledge base that survives across different conversation sessions. By enabling the agent to proactively save, organize, and recall critical information—such as research findings, architectural decisions, and complex debugging solutions—it effectively solves the problem of context loss in long-term projects. This skill transforms the AI from a stateless assistant into a knowledgeable collaborator that maintains a continuous understanding of your specific codebase and project history.

Use Cases

  • Preserving Technical Research: Save deep-dive investigations into third-party libraries or complex APIs to avoid redundant research in future tasks.
  • Documenting Architectural Rationale: Record the reasoning behind specific design patterns or system architecture decisions to ensure long-term maintainability and team alignment.
  • Resuming Multi-day Projects: Log the current state, blockers, and next steps of an ongoing task to seamlessly resume work after a break or session timeout.
  • Building a Project-Specific 'Gotchas' Database: Catalog non-obvious bugs, environment-specific issues, and their solutions to speed up future troubleshooting within the same codebase.
  • Organizing Knowledge Proactively: Automatically categorize and consolidate scattered insights into a clean, searchable folder structure for efficient retrieval using ripgrep.
nameagent-memory
description"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', 'stop here', 'pause this', 'record this', 'log this'. Also use proactively when discovering valuable findings worth preserving."

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:

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.

Required:

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

Optional:

---
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:

# 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)
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
    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 self-contained notes: Include full context so the reader needs no prior knowledge to understand and act on the content
  2. Keep summaries decisive: Reading the summary should tell you if you need the details
  3. Stay current: Update or delete outdated information
  4. 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.