Locate and load GEMINI_API_KEY from environment variables and .env files.
npx skills add https://github.com/wollfoo/setup-opencode --skill common
Please help me install this Agent Skill. Skill: common Source: https://github.com/wollfoo/setup-opencode/tree/main/skills/common Command: npx skills add https://github.com/wollfoo/setup-opencode --skill common
This skill centralizes and streamlines the discovery and loading of GEMINI_API_KEY from multiple sources—environment variables and layered .env files—reducing setup friction and avoiding credential misconfigurations.
Import from api_key_helper and retrieve the API key or client: from api_key_helper import get_api_key_or_exit, get_client api_key = get_api_key_or_exit() client = get_client()
High-intent search queries and answers about installing and using this skill.
You can switch between Vertex AI and AI Studio endpoints using a single configuration check within the skill. It retrieves the appropriate client via get_client, ensuring proper endpoint routing for Gemini integrations.
The best way to securely configure a Gemini API key in a team environment is using layered .env files. This skill centralizes key discovery across these locations, reducing setup friction and avoiding credential misconfigurations.
Your Gemini integration fails with a missing API key error when GEMINI_API_KEY is absent from all searched locations. The skill provides actionable error messages and guidance for setting up the key via environment variables or .env files.
Yes, you can use environment variables instead of .env files for Gemini authentication. The skill's flexible key discovery automatically searches the environment first before checking project root and skill-specific .env locations.
You need a single configuration check to switch between Vertex AI and AI Studio endpoints. The skill handles the endpoint selection automatically when you retrieve the client using the get_client function.
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