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.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionpara-memory-filesExecute the skills CLI command in your project's root directory to begin installation:
Fetches para-memory-files from paperclipai/paperclip 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 para-memory-files. Access via /para-memory-files 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.
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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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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.
$AGENT_HOME/life/ -- PARA)Entity-based storage. Each entity gets a folder with two tiers:
summary.md -- quick context, load first.items.yaml -- atomic facts, load on demand.$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:
Fact rules:
items.yaml.summary.md from active facts.status: superseded, add superseded_by).$AGENT_HOME/life/archives/.When to create an entity:
For the atomic fact YAML schema and memory decay rules, see references/schemas.md.
$AGENT_HOME/memory/YYYY-MM-DD.md)Raw timeline of events -- the "when" layer.
$AGENT_HOME/MEMORY.md)How the user operates -- patterns, preferences, lessons learned.
Memory does not survive session restarts. Files do.
$AGENT_HOME/memory/YYYY-MM-DD.md or the relevant entity file.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.
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.
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
para-memory-files is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: para-memory-files is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for para-memory-files matched our evaluation — installs cleanly and behaves as described in the markdown.
We added para-memory-files from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
para-memory-files reduced setup friction for our internal harness; good balance of opinion and flexibility.
para-memory-files reduced setup friction for our internal harness; good balance of opinion and flexibility.
para-memory-files fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for para-memory-files matched our evaluation — installs cleanly and behaves as described in the markdown.
I recommend para-memory-files for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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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