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Agent Memory Systems

Checked
davila7·vlatest·agents·MIT

Davila7's memory systems enable agents to store, retrieve, and utilize complex information across extended interactions for improved performance.

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 davila7/claude-code-templates --skill agent-memory-systems -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

davila7

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 davila7/claude-code-templates at 79182c51fb.

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

Commit
79182c51fb
Manifest
cli-tool/components/skills/ai-research/agent-memory-systems/SKILL.md
Scanned
1 file, 68 lines
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 davila7-agent-memory-systems skill provides AI agents with advanced memory management capabilities, enabling them to retain and recall information across interactions. It supports both short-term and long-term memory systems, allowing for context-aware responses and persistent data storage.

When to use it

  • When building an AI agent that needs to remember user preferences or past conversations.
  • For applications requiring multi-turn dialogue with consistent context retention.
  • In scenarios where the agent must store and retrieve structured data over time.
  • When developing agents that need to learn from previous interactions for improved future performance.

Key capabilities

  • Short-term memory for tracking immediate conversation context.
  • Long-term memory for storing persistent user data or preferences.
  • Context-aware retrieval of stored information during new interactions.
  • Integration with external storage systems for scalable memory management.

Example prompts

  • "Remember that the user prefers dark mode in their settings."
  • "Retrieve the last project the user mentioned and provide an update."
  • "Store this document for future reference when the user asks about it again."

Tips & gotchas

  • Ensure proper configuration of memory retention policies to avoid data overload.
  • Be mindful of privacy considerations when storing user-specific information.