super-search_skill

This skill helps you quickly recall past coding work and decisions by querying Supermemory across sessions and repositories.
  • JavaScript

2.2k

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill supermemoryai/claude-supermemory --skill super-search

  • SKILL.md1.4 KB

Overview

This skill lets you search your coding memory to recall past sessions, implementation decisions, and saved project or personal notes. It is built in JavaScript and designed to retrieve timestamped, relevance-scored results so you can quickly find what you or your team discussed or implemented. Use it to reconstruct previous work, confirm choices, or recover details from earlier conversations.

How this skill works

Run a search with a natural-language query and choose a scope: personal sessions, project/repo memories, or both. The system returns formatted results with timestamps and relevance scores so you can prioritize hits. Results include snippets of matched memory and context; you can refine the query and rerun the search to narrow or broaden results.

When to use it

  • You want to recall what you or the team worked on previously (e.g., yesterday or last week).
  • You need to find how a feature or integration was implemented in a past session.
  • You want to retrieve personal preferences or coding style notes you saved earlier.
  • You need project-specific decisions or design rationale made by team members.
  • You are reconstructing past troubleshooting steps or debugging notes.

Best practices

  • Start with a clear, short natural-language query and add key terms (feature names, file names, or error codes).
  • Use scope flags to limit results: personal memories for your notes, repo/project for team-wide decisions, or both for a comprehensive search.
  • Inspect timestamps and relevance scores to prioritize the most recent or most relevant entries.
  • Iteratively refine queries when results are too broad—add context like dates, component names, or team member identifiers.
  • Treat returned snippets as pointers; open the full session or note for complete context before acting.

Example use cases

  • Ask what you worked on yesterday to recover unfinished tasks and file references.
  • Search how authentication was implemented to find code snippets, design notes, or decisions from the team.
  • Retrieve your saved coding preferences and style guidelines to keep new code consistent.
  • Find previous debugging steps and error reproductions when returning to a recurring bug.
  • Locate design discussions or architecture trade-offs recorded during planning sessions.

FAQ

Yes. Use the personal/user scope to search only your saved sessions and preferences.

How are results ranked?

Results include relevance scores and timestamps; higher scores indicate closer matches to your query and recent entries are shown to help prioritize.

Built by
VeilStrat
AI signals for GTM teams
© 2026 VeilStrat. All rights reserved.All systems operational