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Python

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video-db·vlatest·backend·MIT

Helps with video, Python as part of developing backend services and APIs workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Installs under a different name. Its SKILL.md names it videodb, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add video-db/skills --skill videodb -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

video-db

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 video-db/skills at b47b587e28.

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

Commit
b47b587e28
Manifest
python/SKILL.md
Scanned
22 files, 7,020 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 provides access to a Python database, enabling AI agents to query and manipulate data stored within. It allows for retrieving specific information, performing calculations based on the data, and updating records as needed. The core functionality revolves around interacting with structured data using Python's capabilities.

When to use it

  • Data Analysis: Extracting trends or insights from a video dataset (e.g., identifying popular content).
  • Content Recommendation: Building personalized recommendations based on user viewing history stored in the database.
  • Automated Reporting: Generating reports summarizing key metrics about videos, such as views, likes, and comments.
  • Inventory Management: Tracking available video assets and their metadata for efficient organization.

Key capabilities

  • Database querying using Python
  • Data retrieval based on specific criteria
  • Data manipulation (updates, insertions)
  • Calculation and aggregation of data
  • Structured data interaction

Example prompts

  • "Retrieve the titles of all videos uploaded in the last week."
  • "Calculate the average view count for videos tagged 'tutorial'."
  • "Update the description of video ID 123 to include a new keyword."
  • “List all videos with more than 1000 likes.”

Tips & gotchas

  • Requires familiarity with Python syntax and database querying concepts.
  • The specific schema (structure) of the database is not defined in this documentation; consult video-db for details.