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Pydantic

Checked
jiatastic·vlatest·backend·MIT

Pydantic validates Python data structures against schemas, ensuring data integrity and simplifying API development.

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 jiatastic/open-python-skills --skill pydantic -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

jiatastic

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 jiatastic/open-python-skills at 41249c879c.

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

Commit
41249c879c
Manifest
skills/pydantic/SKILL.md
Scanned
3 files, 131 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 leverages Pydantic, a Python library used for data validation and parsing. It allows AI agents to define schemas for structured data, validate incoming data against those schemas, and parse data into Python objects with type safety. This ensures data integrity and simplifies downstream processing within the agent's workflow.

When to use it

  • Data Validation: When receiving user input or external API responses that need to be validated before further processing (e.g., validating a JSON payload for an order).
  • Configuration Management: To enforce specific data structures and types when loading configuration files, preventing errors due to incorrect formatting.
  • API Integration: When interacting with APIs that return structured data, ensuring the agent correctly interprets and handles the responses.
  • Data Transformation: To reliably transform raw data into a consistent format for analysis or other tasks.

Key capabilities

  • Data validation using Pydantic schemas
  • Parsing of data into Python objects based on defined schemas
  • Type safety enforcement during data processing
  • Schema definition and management

Example prompts

  • "Validate this JSON payload against the 'Order' schema: { ... }"
  • "Parse this string as a 'User' object using the User schema."
  • “Create a Pydantic model for an invoice with fields for date, amount, and customer.”

Tips & gotchas

  • Requires Python 3.7 or higher to be installed in the agent’s environment.
  • The agent needs access to the relevant Pydantic schemas; ensure these are provided or accessible.