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Agent Openai Memory

Checked
databricks·vlatest·ai-ml

Leverages OpenAI's models to store, retrieve, and utilize conversational context for enhanced agent reasoning.

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 databricks/app-templates --skill agent-openai-memory -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

databricks

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 databricks/app-templates at 74c0cd0f66.

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

Commit
74c0cd0f66
Manifest
.claude/skills/agent-openai-memory/SKILL.md
Scanned
1 file, 159 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

This skill provides OpenAI memory capabilities to AI agents. It allows agents to persist and retrieve information from previous interactions, enabling more contextually aware and coherent conversations. This functionality enhances an agent's ability to remember details and build upon past exchanges.

When to use it

  • Long-running conversations: When you need the agent to recall earlier parts of a lengthy discussion.
  • Complex tasks with dependencies: For scenarios where the agent needs to track steps or information across multiple interactions (e.g., planning a trip).
  • Personalized experiences: To allow an agent to remember user preferences and tailor responses accordingly.
  • Knowledge base integration: To enable agents to recall facts from previous sessions, effectively creating a short-term memory of the interaction.

Key capabilities

  • Persists conversation history.
  • Retrieves relevant information from past interactions.
  • Enhances contextual awareness for AI agents.

Example prompts

  • "Summarize our discussion so far."
  • "What were my preferences regarding [topic]?"
  • "Continue where we left off in planning the project."

Tips & gotchas

The effectiveness of this skill depends on the quality and relevance of the information stored in memory. Consider setting limits on memory size to prevent performance degradation or excessive costs.