memory-defrag

basicmachines-co/basic-memory-skills · updated Apr 8, 2026

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$npx skills add https://github.com/basicmachines-co/basic-memory-skills --skill memory-defrag
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summary

Reorganize memory files for clarity, efficiency, and relevance. Like filesystem defragmentation but for knowledge.

skill.md

Memory Defrag

Reorganize memory files for clarity, efficiency, and relevance. Like filesystem defragmentation but for knowledge.

When to Run

  • Periodic: Weekly or biweekly via cron (recommended)
  • On demand: User asks to clean up, reorganize, or defrag memory
  • Threshold: When MEMORY.md exceeds ~500 lines or daily notes accumulate without consolidation

Process

1. Audit Current State

Inventory all memory files:

MEMORY.md           — long-term memory
memory/             — daily notes, tasks, topical files
memory/tasks/       — active and completed tasks

For each file, note: line count, last modified, topic coverage, staleness.

2. Identify Problems

Look for these common issues:

Problem Signal Fix
Bloated file >300 lines, covers many topics Split into focused files
Duplicate info Same fact in multiple places Consolidate to one location
Stale entries References to completed work, old dates, resolved issues Remove or archive
Orphan files Files in memory/ never referenced or updated Review, merge, or remove
Inconsistencies Contradictory information across files Resolve to ground truth
Poor organization Related info scattered across files Restructure by topic
Recursive nesting memory/memory/memory/... directories Delete nested dirs (indexer bug artifact)

3. Plan Changes

Before making edits, write a brief plan:

## Defrag Plan
- [ ] Split MEMORY.md "Key People" section → memory/people.md
- [ ] Remove completed tasks older than 30 days from memory/tasks/
- [ ] Merge memory/bm-marketing-ideas.md into memory/competitive/
- [ ] Update stale project status entries in MEMORY.md

4. Execute

Apply changes one at a time:

  • Split: Extract sections from large files into focused topical files
  • Merge: Combine related small files into coherent documents
  • Prune: Remove information that is no longer relevant or accurate
  • Restructure: Move files to appropriate directories, rename for clarity
  • Update: Fix outdated facts, dates, statuses

5. Verify & Log

After changes:

  • Verify no information was lost (compare before/after)
  • Update any cross-references between files
  • Log what was done in today's daily note:
## Memory Defrag (HH:MM)
- Files reviewed: N
- Split: [list]
- Merged: [list]
- Pruned: [list]
- Net result: X files, Y total lines (was Z lines)

Guidelines

  • Preserve raw daily notes. Don't delete or modify memory/YYYY-MM-DD.md files — they're the audit trail.
  • Target 15-25 focused files. Too few means bloated files; too many means fragmentation. Aim for the sweet spot.
  • File names should be scannable. Use descriptive names: people.md, project-status.md, competitive-landscape.md — not notes-2.md.
  • Don't over-organize. One level of directories is usually enough. memory/tasks/ and memory/competitive/ are fine; memory/work/projects/active/basic-memory/notes/ is not.
  • Completed tasks: Tasks with status: done older than 14 days can be removed. Their insights should already be in MEMORY.md via reflection.
  • Ask before destructive changes. If uncertain whether information is still relevant, keep it with a (review needed) tag rather than deleting.
how to use memory-defrag

How to use memory-defrag on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add memory-defrag
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/basicmachines-co/basic-memory-skills --skill memory-defrag

The skills CLI fetches memory-defrag from GitHub repository basicmachines-co/basic-memory-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/memory-defrag

Reload or restart Cursor to activate memory-defrag. Access the skill through slash commands (e.g., /memory-defrag) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

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

Ratings

4.851 reviews
  • Advait Johnson· Dec 24, 2024

    memory-defrag is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Dev Thompson· Dec 20, 2024

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

  • Ren Jackson· Dec 16, 2024

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

  • William Thompson· Dec 12, 2024

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

  • Neel Desai· Nov 23, 2024

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

  • Advait Lopez· Nov 15, 2024

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

  • Evelyn Rahman· Nov 11, 2024

    memory-defrag is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Layla Jain· Oct 14, 2024

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

  • Advait Sharma· Oct 6, 2024

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

  • Sakura Mehta· Oct 2, 2024

    Useful defaults in memory-defrag — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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