Reorganize memory files for clarity, efficiency, and relevance. Like filesystem defragmentation but for knowledge.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionmemory-defragExecute the skills CLI command in your project's root directory to begin installation:
Fetches memory-defrag from basicmachines-co/basic-memory-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate memory-defrag. Access via /memory-defrag in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Reorganize memory files for clarity, efficiency, and relevance. Like filesystem defragmentation but for knowledge.
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.
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) |
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
Apply changes one at a time:
After changes:
## Memory Defrag (HH:MM)
- Files reviewed: N
- Split: [list]
- Merged: [list]
- Pruned: [list]
- Net result: X files, Y total lines (was Z lines)
memory/YYYY-MM-DD.md files — they're the audit trail.people.md, project-status.md, competitive-landscape.md — not notes-2.md.memory/tasks/ and memory/competitive/ are fine; memory/work/projects/active/basic-memory/notes/ is not.status: done older than 14 days can be removed. Their insights should already be in MEMORY.md via reflection.(review needed) tag rather than deleting.Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
memory-defrag is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
memory-defrag reduced setup friction for our internal harness; good balance of opinion and flexibility.
memory-defrag has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: memory-defrag is the kind of skill you can hand to a new teammate without a long onboarding doc.
memory-defrag has been reliable in day-to-day use. Documentation quality is above average for community skills.
memory-defrag reduced setup friction for our internal harness; good balance of opinion and flexibility.
memory-defrag is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: memory-defrag is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend memory-defrag for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in memory-defrag — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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