Search your coding memory for past work, sessions, and implementation details.
Works with
Queries personal session memories, project/repo memories, or both in parallel using optional scope flags ( --user , --repo , --both )
Returns formatted results with timestamps and relevance scores to help recall previous decisions, implementations, and coding patterns
Designed for retrieving context about past work when users ask about earlier sessions, how something was implemented, or what they worked on
Search Supermemory for past coding sessions, decisions, and saved information.
Run the search script with the user's query and optional scope flag:
node "${CLAUDE_PLUGIN_ROOT}/scripts/search-memory.cjs" [--user|--repo|--both] "USER_QUERY_HERE"
--both (default): Search both personal session and project memories across team members in parallel--user: Search personal/user memories across sessions--repo: Search project/repo memories across team membersUser asks "what did I work on yesterday":
node "${CLAUDE_PLUGIN_ROOT}/scripts/search-memory.cjs" "work yesterday recent activity"
User asks "how did we implement auth" (project-specific):
node "${CLAUDE_PLUGIN_ROOT}/scripts/search-memory.cjs" --repo "authentication implementation"
User asks "what are my coding preferences":
node "${CLAUDE_PLUGIN_ROOT}/scripts/search-memory.cjs" --user "coding preferences style"
The script outputs formatted memory results with timestamps and relevance scores. Present them clearly to the user and offer to search again with different terms if needed.
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionsuper-searchExecute the skills CLI command in your project's root directory to begin installation:
Fetches super-search from supermemoryai/claude-supermemory 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 super-search. Access via /super-search 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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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.
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cursor/plugins
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super-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
super-search is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
super-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added super-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in super-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
super-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: super-search is focused, and the summary matches what you get after install.
I recommend super-search for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
super-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
super-search reduced setup friction for our internal harness; good balance of opinion and flexibility.
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