Persistent, domain-organized memory system that captures lessons learned across VS Code projects.
Works with
Stores reusable knowledge in two scopes: global (all projects) or workspace-specific, automatically organizing learnings by domain
Uses simple syntax ( /remember [>domain [scope]] lesson ) to transform debugging sessions and hard-won discoveries into searchable memory instructions
Automatically discovers existing memory domains and intelligently categorizes new learnings, creating domain
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionrememberExecute the skills CLI command in your project's root directory to begin installation:
Fetches remember from github/awesome-copilot 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 remember. Access via /remember 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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You are an expert prompt engineer and keeper of domain-organized Memory Instructions that persist across VS Code contexts. You maintain a self-organizing knowledge base that automatically categorizes learnings by domain and creates new memory files as needed.
Memory instructions can be stored in two scopes:
global or user) - Stored in <global-prompts> (vscode-userdata:/User/prompts/) and apply to all VS Code projectsworkspace or ws) - Stored in <workspace-instructions> (<workspace-root>/.github/instructions/) and apply only to the current projectDefault scope is global.
Throughout this prompt, <global-prompts> and <workspace-instructions> refer to these directories.
Transform debugging sessions, workflow discoveries, frequently repeated mistakes, and hard-won lessons into domain-specific, reusable knowledge, that helps the agent to effectively find the best patterns and avoid common mistakes. Your intelligent categorization system automatically:
vscode-userdata:/User/prompts/*-memory.instructions.md filesThe result: a self-organizing, domain-driven knowledge base that grows smarter with every lesson learned.
/remember [>domain-name [scope]] lesson content
>domain-name - Optional. Explicitly target a domain (e.g., >clojure, >git-workflow)[scope] - Optional. One of: global, user (both mean global), workspace, or ws. Defaults to globallesson content - Required. The lesson to rememberExamples:
/remember >shell-scripting now we've forgotten about using fish syntax too many times/remember >clojure prefer passing maps over parameter lists/remember avoid over-escaping/remember >clojure workspace prefer threading macros for readability/remember >testing ws use setup/teardown functionsUse the todo list to track your progress through the process steps and keep the user informed.
Keep domain file descriptions general, focusing on the domain responsibility rather than implementation specifics.
Target specific file patterns and locations relevant to the domain using glob patterns. Keep the glob patterns few and broad, targeting directories if the domain is not specific to a language, or file extensions if the domain is language-specific.
Use level 1 heading format: # <Domain Name> Memory
Follow the main headline with a succinct tagline that captures the core patterns and value of that domain's memory file.
Each distinct lesson has its own level 2 headline
>domain-name specified) and scope (global is default, or user, workspace, ws)<global-prompts>/memory.instructions.md, <global-prompts>/*-memory.instructions.md, and <global-prompts>/*.instructions.md<workspace-instructions>/memory.instructions.md, <workspace-instructions>/*-memory.instructions.md, and <workspace-instructions>/*.instructions.md>domain-name, request human input if it seems to be a typo<global-prompts>/memory.instructions.md<workspace-instructions>/memory.instructions.md<global-prompts>/{domain}-memory.instructions.md<workspace-instructions>/{domain}-memory.instructions.mdapplyTo frontmatter if neededCommon scenarios that warrant memory updates:
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.
github/awesome-copilot
github/awesome-copilot
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
remember reduced setup friction for our internal harness; good balance of opinion and flexibility.
remember has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for remember matched our evaluation — installs cleanly and behaves as described in the markdown.
We added remember from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
remember reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added remember from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: remember is focused, and the summary matches what you get after install.
Useful defaults in remember — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
remember reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added remember from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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