agent-memory

yamadashy/repomix · updated Apr 8, 2026

$npx skills add https://github.com/yamadashy/repomix --skill agent-memory
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summary

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

skill.md

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  • Remove outdated or superseded information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.

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:

---
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 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.

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.643 reviews
  • Mei Kapoor· Dec 28, 2024

    We added agent-memory from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Layla Garcia· Dec 24, 2024

    I recommend agent-memory for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Yusuf Tandon· Dec 20, 2024

    Keeps context tight: agent-memory is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Ganesh Mohane· Dec 12, 2024

    Keeps context tight: agent-memory is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Zara Khan· Dec 4, 2024

    agent-memory has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Zara Torres· Nov 23, 2024

    agent-memory fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Tariq Dixit· Nov 19, 2024

    Solid pick for teams standardizing on skills: agent-memory is focused, and the summary matches what you get after install.

  • Dev Kapoor· Nov 11, 2024

    Registry listing for agent-memory matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Rahul Santra· Nov 3, 2024

    Registry listing for agent-memory matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Pratham Ware· Oct 22, 2024

    agent-memory reduced setup friction for our internal harness; good balance of opinion and flexibility.

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