para-memory-files▌
paperclipai/paperclip · updated Apr 8, 2026
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Persistent, file-based memory organized by Tiago Forte's PARA method. Three layers: a knowledge graph, daily notes, and tacit knowledge. All paths are relative to $AGENT_HOME.
PARA Memory Files
Persistent, file-based memory organized by Tiago Forte's PARA method. Three layers: a knowledge graph, daily notes, and tacit knowledge. All paths are relative to $AGENT_HOME.
Three Memory Layers
Layer 1: Knowledge Graph ($AGENT_HOME/life/ -- PARA)
Entity-based storage. Each entity gets a folder with two tiers:
summary.md-- quick context, load first.items.yaml-- atomic facts, load on demand.
$AGENT_HOME/life/
projects/ # Active work with clear goals/deadlines
<name>/
summary.md
items.yaml
areas/ # Ongoing responsibilities, no end date
people/<name>/
companies/<name>/
resources/ # Reference material, topics of interest
<topic>/
archives/ # Inactive items from the other three
index.md
PARA rules:
- Projects -- active work with a goal or deadline. Move to archives when complete.
- Areas -- ongoing (people, companies, responsibilities). No end date.
- Resources -- reference material, topics of interest.
- Archives -- inactive items from any category.
Fact rules:
- Save durable facts immediately to
items.yaml. - Weekly: rewrite
summary.mdfrom active facts. - Never delete facts. Supersede instead (
status: superseded, addsuperseded_by). - When an entity goes inactive, move its folder to
$AGENT_HOME/life/archives/.
When to create an entity:
- Mentioned 3+ times, OR
- Direct relationship to the user (family, coworker, partner, client), OR
- Significant project or company in the user's life.
- Otherwise, note it in daily notes.
For the atomic fact YAML schema and memory decay rules, see references/schemas.md.
Layer 2: Daily Notes ($AGENT_HOME/memory/YYYY-MM-DD.md)
Raw timeline of events -- the "when" layer.
- Write continuously during conversations.
- Extract durable facts to Layer 1 during heartbeats.
Layer 3: Tacit Knowledge ($AGENT_HOME/MEMORY.md)
How the user operates -- patterns, preferences, lessons learned.
- Not facts about the world; facts about the user.
- Update whenever you learn new operating patterns.
Write It Down -- No Mental Notes
Memory does not survive session restarts. Files do.
- Want to remember something -> WRITE IT TO A FILE.
- "Remember this" -> update
$AGENT_HOME/memory/YYYY-MM-DD.mdor the relevant entity file. - Learn a lesson -> update AGENTS.md, TOOLS.md, or the relevant skill file.
- Make a mistake -> document it so future-you does not repeat it.
- On-disk text files are always better than holding it in temporary context.
Memory Recall -- Use qmd
Use qmd rather than grepping files:
qmd query "what happened at Christmas" # Semantic search with reranking
qmd search "specific phrase" # BM25 keyword search
qmd vsearch "conceptual question" # Pure vector similarity
Index your personal folder: qmd index $AGENT_HOME
Vectors + BM25 + reranking finds things even when the wording differs.
Planning
Keep plans in timestamped files in plans/ at the project root (outside personal memory so other agents can access them). Use qmd to search plans. Plans go stale -- if a newer plan exists, do not confuse yourself with an older version. If you notice staleness, update the file to note what it is supersededBy.
How to use para-memory-files on Cursor
AI-first code editor with Composer
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 para-memory-files
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches para-memory-files from GitHub repository paperclipai/paperclip and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate para-memory-files. Access the skill through slash commands (e.g., /para-memory-files) 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
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★41 reviews- ★★★★★Meera Desai· Dec 28, 2024
para-memory-files is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Kofi Tandon· Dec 8, 2024
Keeps context tight: para-memory-files is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Sophia Brown· Nov 27, 2024
Registry listing for para-memory-files matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Sophia Chen· Nov 23, 2024
We added para-memory-files from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Amina Mensah· Nov 19, 2024
para-memory-files reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Evelyn Sanchez· Oct 18, 2024
para-memory-files reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Nia Gupta· Oct 14, 2024
para-memory-files fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Yusuf Agarwal· Oct 10, 2024
Registry listing for para-memory-files matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Oshnikdeep· Sep 25, 2024
I recommend para-memory-files for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Amelia Verma· Sep 13, 2024
Solid pick for teams standardizing on skills: para-memory-files is focused, and the summary matches what you get after install.
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