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Dart Memory

Checked
dhruvanbhalara·vlatest·other·MIT

Dart-Memory recalls and synthesizes information from diverse sources to answer complex questions and generate creative content.

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 dhruvanbhalara/skills --skill dart-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

dhruvanbhalara

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 dhruvanbhalara/skills at a74a6fbe04.

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

Scanned
1 file, 31 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 dart-memory skill provides a way to store and retrieve data using Dart's memory management capabilities. It allows AI agents to persist information across interactions, effectively giving them short-term recall. This enables more complex reasoning and task completion by remembering previous steps or user preferences.

When to use it

  • Remembering User Preferences: Store a user’s preferred language or style for personalized responses.
  • Tracking Task Progress: Keep track of the steps completed in a multi-stage process, like booking a flight.
  • Maintaining Context Across Turns: Recall previous conversation turns to provide more relevant and coherent replies.
  • Storing Intermediate Results: Save results from calculations or API calls for later use in a complex workflow.

Key capabilities

  • Data persistence across interactions
  • Dart memory management integration
  • Short-term recall functionality

Example prompts

  • "Remember that I prefer responses in French."
  • "Save the current date and time as 'last_accessed'."
  • "What was the last value I saved for 'flight_number'?"

Tips & gotchas

The skill relies on Dart's memory management, so be mindful of potential limitations regarding data size and retention duration. Consider how frequently the agent will be used to determine appropriate storage strategies.