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Generate Models

Checked
haibaraaiaptx·vlatest·data·MIT

Creates diverse statistical models (e.g., regression, classification) from provided data for analysis and prediction.

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 haibaraaiaptx/frontend-openapi-skills --skill generate-models -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

haibaraaiaptx

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 haibaraaiaptx/frontend-openapi-skills at 0d2927f8b0.

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

Commit
0d2927f8b0
Manifest
skills/generate-models/SKILL.md
Scanned
1 file, 201 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 AI agents to generate models. It's designed for creating new model definitions, likely based on provided specifications or examples. The generated models can then be used in other processes, such as code generation or data processing pipelines. This capability streamlines the creation of complex systems by automating a key component.

When to use it

  • Rapid Prototyping: Quickly create initial versions of models for testing and experimentation without manual coding.
  • Automated Code Generation: Generate model definitions programmatically as part of a larger code generation workflow.
  • Data Pipeline Setup: Automatically define data models needed for processing and transforming datasets.
  • API Integration: Create models that represent API responses or requests, simplifying integration with external services.

Key capabilities

  • Model Generation: Creates new model definitions based on given inputs.
  • Specification-Based Generation: Generates models from provided specifications.
  • Example-Based Generation: Generates models using example data as a guide.

Example prompts

  • "Generate a model for an e-commerce product with fields for name, price, and description."
  • "Create a model based on this OpenAPI specification: [paste specification here]"
  • "Generate a model representing the following JSON structure: { 'user_id': 123, 'timestamp': '2024-01-01' }"

Tips & gotchas

The quality of the generated models depends heavily on the clarity and completeness of the provided specifications or examples. Ensure that any input data is well-structured and accurately represents the desired model schema.