Package
google-gemini/gemini-skills
Skills for the Gemini API, SDK and model/agent interactions
Trust means
Trust score is a heuristic blend of popularity, freshness, structure quality, and safety penalties. Useful for ranking, not a guarantee.
Risk means
Risk is generated by automated scans of skills, files, and allowed tools. It is not the same thing as a human security review.
Review status
Auto-scanned only. High-risk signals exist, so manual review is strongly recommended before install.
Risk: High (pattern: destructive, pattern: network/exfil)
Stars
3,114
Forks
274
Skills
4
Files
13
Suitable for
People who want packaged, installable skill bundles with enough context to inspect the workflow before adding it to their agent stack.
Not suitable for
Not the right fit if you only want raw repo content without install guidance or if your team refuses packaged workflows altogether.
Install prerequisites
What to verify before touching install
- Read the starter skill and confirm the package solves a real workflow, not just a vague collection of prompts.
- Check file count, allowed tools, and install path expectations before bringing it into your environment.
- Make sure the agent runtime you use supports the package install flow you plan to follow.
Recommended first read
vertex-ai-api-dev
Guides the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
Path: skills/vertex-ai-api-dev
Risk level: Low
After install
How to verify it actually works
Core skills
What this package actually helps you do
Guides the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
skills/vertex-ai-api-dev · 10 files
Use this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. This skill covers the Interactions API, the recommended way to use Gemini models and agents in Python and TypeScript.
skills/gemini-interactions-api · 1 file
Use this skill when building applications with Gemini models, Gemini API, working with multimodal content (text, images, audio, video), implementing function calling, using structured outputs, or needing current model specifications. Covers SDK usage (google-genai for Python, @google/genai for JavaScript/TypeScript, com.google.genai:google-genai for Java, google.golang.org/genai for Go), model selection, and API capabilities.
skills/gemini-api-dev · 1 file
Use this skill when building real-time, bidirectional streaming applications with the Gemini Live API. Covers WebSocket-based audio/video/text streaming, voice activity detection (VAD), native audio features, function calling, session management, ephemeral tokens for client-side auth, and all Live API configuration options. SDKs covered - google-genai (Python), @google/genai (JavaScript/TypeScript).
skills/gemini-live-api-dev · 1 file
Package contents
Folders and files
vertex-ai-api-dev
skills/vertex-ai-api-dev
Guides the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
- SKILL.md.md
- references/advanced_features.md.md
- references/bounding_box.md.md
- references/embeddings.md.md
- references/live_api.md.md
- references/media_generation.md.md
- references/model_tuning.md.md
- references/safety.md.md
- references/structured_and_tools.md.md
- references/text_and_multimodal.md.md
gemini-interactions-api
skills/gemini-interactions-api
Use this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. This skill covers the Interactions API, the recommended way to use Gemini models and agents in Python and TypeScript.
- SKILL.md.md
gemini-api-dev
skills/gemini-api-dev
Use this skill when building applications with Gemini models, Gemini API, working with multimodal content (text, images, audio, video), implementing function calling, using structured outputs, or needing current model specifications. Covers SDK usage (google-genai for Python, @google/genai for JavaScript/TypeScript, com.google.genai:google-genai for Java, google.golang.org/genai for Go), model selection, and API capabilities.
- SKILL.md.md
gemini-live-api-dev
skills/gemini-live-api-dev
Use this skill when building real-time, bidirectional streaming applications with the Gemini Live API. Covers WebSocket-based audio/video/text streaming, voice activity detection (VAD), native audio features, function calling, session management, ephemeral tokens for client-side auth, and all Live API configuration options. SDKs covered - google-genai (Python), @google/genai (JavaScript/TypeScript).
- SKILL.md.md
Last step
Install only after the checks above
If the package fits your workflow, the starter skill makes sense, and the auto-scan signals are acceptable for your environment, then use the exact install command below.
Install command
npx skills add google-gemini/gemini-skills
Claude Code
Copy to .claude/skills/
GitHub Copilot
Copy to .github/skills/
Codex CLI
Copy to .agents/skills/
Gemini CLI
Copy to .gemini/skills/
Community Signals
What users think
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