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Mem Search

Checked
thedotmack·vlatest·other·Apache-2.0

Quickly retrieves relevant information from past conversations and external knowledge sources to inform responses.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add thedotmack/claude-mem --skill mem-search -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

thedotmack

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned thedotmack/claude-mem at 2c177c776e.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
2c177c776e
Manifest
cowork/skills/mem-search/SKILL.md
Scanned
3 files, 219 lines
Copies in repo
3 — all of them scanned
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The Mem Search skill enables an AI agent to retrieve relevant information from past conversations and external knowledge sources, specifically focusing on previous work across all sessions. It follows a three-step workflow: search for indexed IDs, filter results using timelines, and then fetch the full details of only the most pertinent items. This allows the agent to provide contextually aware responses based on prior interactions and project history.

When to use it

This skill is best used in scenarios where you need information from past sessions, such as:

  • When a user asks about previously addressed issues ("Did we already fix this?").
  • To recall how similar problems were solved in the past ("How did we solve X last time?").
  • To understand what transpired during previous interactions ("What happened last week?").
  • For quickly referencing project history and decisions.

Key capabilities

  • Search: Retrieves a list of indexed IDs based on a search query, limit, and project filter.
  • Timeline: Provides context around specific results by retrieving items before and after an anchor point (either specified or automatically found).
  • Fetch: Retrieves the full details of selected observation IDs for comprehensive review.
  • Supports filtering by type ("observations", "sessions", or "prompts") and observation type (bugfix, feature, decision, discovery, change).
  • Allows date range filtering using dateStart and dateEnd.
  • Offers ordering options like "date_desc," "date_asc," and "relevance."

Example prompts

  • "Search for authentication issues in my-project and show me the last 20 results."
  • "What was the timeline around observation ID 11131?"
  • "Find bug fixes related to 'authentication' within the last week in project my-project."

Tips & gotchas

  • Always follow the three-step workflow (search -> filter -> fetch). Skipping filtering can lead to unnecessary token usage.
  • The skill is designed for retrieving information from previous sessions, not the current conversation context.
  • When fetching details, use get_observations with multiple IDs in a single request whenever possible to optimize efficiency.