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Sqlmodel Expert

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bilalmk·vlatest·database

This SQLModel Expert provides in-depth knowledge and assistance for utilizing SQLAlchemy's ORM extension, SQLModel, streamlining database interactions.

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 bilalmk/todo_correct --skill sqlmodel-expert -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

bilalmk

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 bilalmk/todo_correct at 8b43aa04bd.

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

Commit
8b43aa04bd
Manifest
.claude/skills/custom/sqlmodel-expert/SKILL.md
Scanned
7 files, 2,394 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

sqlmodel-expert

What it does

This skill enables AI agents to interact with databases using SQLModel, a Python library that combines SQLAlchemy and Pydantic. It allows agents to define data models, execute database queries, and manage persistent storage directly within their code execution environment.

When to use it

  • Data Persistence: When an agent needs to save conversation history, user preferences, or generated reports to a local database.
  • Complex Queries: For retrieving specific datasets from structured tables that require filtering, joining, or aggregating beyond simple key-value lookups.
  • Schema Management: When dynamically creating or modifying database tables based on evolving application requirements during runtime.
  • Integration with Python Workflows: To seamlessly bridge data analysis tasks with database storage without switching between different tools or languages.

Key capabilities

  • Define SQLAlchemy-based models using Pydantic validation rules.
  • Execute raw SQL queries and parameterized statements safely.
  • Manage session lifecycles for efficient database connections.
  • Perform CRUD (Create, Read, Update, Delete) operations on tables automatically.
  • Validate data integrity before committing changes to the database.

Example prompts

  • "Create a new table called tasks with columns for title, description, and due date, then insert three sample entries."
  • "Query the database to find all tasks that are due this week and return them as a JSON list."
  • "Update the status of any task marked as 'in progress' to 'completed' if its due date is in the past."

Tips & gotchas

Ensure your AI agent has write access to the file system where the SQLite database (or other supported driver) resides, as SQLModel requires direct disk access to initialize tables. Be cautious with dynamic schema changes; always validate that new columns align with existing data constraints before executing ALTER TABLE statements.