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Google Genai Sdk Python

Checked
cnemri·vlatest·backend·MIT

Provides Python guidance and assistance for developing backend services and APIs.

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 cnemri/google-genai-skills --skill google-genai-sdk-python -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

cnemri

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Live repository

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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 cnemri/google-genai-skills at 7277476f92.

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Commit
7277476f92
Manifest
skills/google-genai-sdk-python/SKILL.md
Scanned
11 files, 399 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.
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About this skill

What it does

This skill provides Python guidance and assistance specifically for developing backend services and APIs that interact with the Gemini API. It helps users write high-quality, idiomatic Python code by referencing relevant documentation and examples related to setup, model selection, text generation, chat functionality, reasoning processes, structured output formats, multimodal inputs, tool usage, media generation, and even access to the raw SDK source code. The skill is designed for use with the google-genai package.

When to use it

  • When you need help installing and authenticating with the Gemini API using Python.
  • When you want guidance on selecting the appropriate Gemini model (Flash, Pro, Lite, Imagen, Veo) for your specific task.
  • If you're building a chatbot application requiring multi-turn conversations and history management.
  • For generating structured output like JSON or utilizing Pydantic models with your Gemini API calls.

Key capabilities

  • Installation and authentication guidance.
  • Model selection recommendations (Flash, Pro, Lite, Imagen, Veo).
  • Text generation assistance including streaming and safety considerations.
  • Chat functionality for multi-turn conversations.
  • Reasoning configuration using thinking_level and thinking_budget.
  • Support for structured output formats like JSON schemas and Pydantic models.
  • Handling of multimodal inputs (images, audio, video, PDFs).
  • Tool integration including function calling and Google Search grounding.
  • Image generation/editing with Imagen and video generation with Veo.

Example prompts

  • "How do I initialize a client for the Gemini API in Python?"
  • "What's the best model to use for generating short, fast responses?"
  • "Can you show me an example of how to structure a chat message with history?"

Tips & gotchas

  • Always use the google-genai package.
  • Use client.models for single requests and client.chats for managing conversations.
  • Refer to google.genai.types for type definitions related to Gemini API interactions.