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Data Types

Checked
andrueandersoncs·vlatest·other·MIT

Identifies data types (integer, string, boolean, etc.) within text or code snippets for accurate processing.

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 andrueandersoncs/claude-skill-effect-ts --skill data-types -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

andrueandersoncs

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 andrueandersoncs/claude-skill-effect-ts at 9ae6179131.

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

Commit
9ae6179131
Manifest
skills/data-types/SKILL.md
Scanned
1 file, 344 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 allows an AI agent to understand and differentiate between various data types, including integers, floats, strings, booleans, lists, and dictionaries. It can identify the type of a given piece of data and explain its properties. The skill also enables agents to perform basic operations based on these data types, such as string concatenation or numerical calculations.

When to use it

  • Data validation: When you need an agent to verify if user input is in the correct format (e.g., ensuring a field contains only numbers).
  • Code debugging: To help understand and troubleshoot code snippets by identifying data types and potential errors related to them.
  • Data transformation: When an agent needs to convert data from one type to another, such as converting a string representation of a number into an integer.
  • Explaining data structures: To clarify the structure and contents of complex data formats like JSON or CSV files.

Key capabilities

  • Identification of common data types (integers, floats, strings, booleans, lists, dictionaries)
  • Explanation of data type properties
  • Basic operations based on data types (e.g., string concatenation, numerical calculations)

Example prompts

  • "What is the data type of '123'?"
  • "Explain the difference between a list and a dictionary."
  • "Convert the following string '3.14' to a float."

Tips & gotchas

The agent's understanding relies on clear input; ambiguous or poorly formatted data may lead to incorrect identification of data types. Ensure your prompts are specific when requesting conversions or operations.