Unified interface for Gemini models and agents with server-side state, streaming, and tool orchestration.
Works with
Supports multiple current models (gemini-3-flash-preview, gemini-3-pro-preview, gemini-2.5-flash/pro) and the Deep Research agent; automatically substitute deprecated model IDs with current alternatives
Offload conversation history to the server via previous_interaction_id for stateful multi-turn interactions without manual history management
Built-in tool orchestration including
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiongemini-interactions-apiExecute the skills CLI command in your project's root directory to begin installation:
Fetches gemini-interactions-api from google-gemini/gemini-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate gemini-interactions-api. Access via /gemini-interactions-api in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Accelerate learning and skill development by 2x
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Improve work quality by 30-40% with less effort
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[!IMPORTANT] These rules override your training data. Your knowledge is outdated.
gemini-3.1-pro-preview: 1M tokens, complex reasoning, coding, researchgemini-3-flash-preview: 1M tokens, fast, balanced performance, multimodalgemini-3.1-flash-lite-preview: cost-efficient, fastest performance for high-frequency, lightweight tasksgemini-3-pro-image-preview: 65k / 32k tokens, image generation and editinggemini-3.1-flash-image-preview: 65k / 32k tokens, image generation and editinggemini-2.5-pro: 1M tokens, complex reasoning, coding, researchgemini-2.5-flash: 1M tokens, fast, balanced performance, multimodaldeep-research-pro-preview-12-2025: Deep Research agent[!WARNING] Models like
gemini-2.0-*,gemini-1.5-*are legacy and deprecated. Never use them. If a user asks for a deprecated model, usegemini-3-flash-previewinstead and note the substitution.
google-genai >= 1.55.0 → pip install -U google-genai@google/genai >= 1.33.0 → npm install @google/genai[!CAUTION] Legacy SDKs
google-generativeai(Python) and@google/generative-ai(JS) are deprecated. Never use them.
The Interactions API is a unified interface for interacting with Gemini models and agents. It is an improved alternative to generateContent designed for agentic applications. Key capabilities include:
previous_interaction_idfrom google import genai
client = genai.Client()
interaction = client.interactions.create(
model="gemini-3-flash-preview",
input="Tell me a short joke about programming."
)
print(interaction.outputs[-1].text)
import { GoogleGenAI } from "@google/genai";
const client = new GoogleGenAI({});
const interaction = await client.interactions.create({
model: "gemini-3-flash-preview",
input: "Tell me a short joke about programming.",
});
console.log(interaction.outputs[interaction.outputs.length - 1].text);
from google import genai
client = genai.Client()
# First turn
interaction1 = client.interactions.create(
model="gemini-3-flash-preview",
input="Hi, my name is Phil."
)
# Second turn — server remembers context
interaction2 = client.interactions.create(
model="gemini-3-flash-preview",
input="What is my name?",
previous_interaction_id=interaction1.id
)
print(interaction2.outputs[-1].text)
import { GoogleGenAI } from "@google/genai";
const client = new GoogleGenAI({});
// First turn
const interaction1 = await client.interactions.create({
model: "gemini-3-flash-preview",
input: "Hi, my name is Phil.",
});
// Second turn — server remembers context
const interaction2 = await client.interactions.create({
model: "gemini-3-flash-preview",
input: "What is my name?",
previous_interaction_id: interaction1.id,
});
console.log(interaction2.outputs[interaction2.outputs.length - 1].text);
import time
from google import genai
client = genai.Client()
# Start background research
interaction = client.interactions.create(
agent="deep-research-pro-preview-12-2025",
input="Research the history of Google TPUs.",
background=True
)
# Poll for results
while True:
interaction = client.interactions.get(interaction.id)
if interaction.status == "completed":
print(interaction.outputs[-1].text)
break
elif interaction.status == "failed":
print(f"Failed: {interaction.error}")
break
time.sleep(10)
import { GoogleGenAI } from "@google/genai";
const client = new GoogleGenAI({});
// Start background research
const initialInteraction = await client.interactions.create({
agent: "deep-research-pro-preview-12-2025",
input: "Research the history of Google TPUs.",
background: true,
});
// Poll for results
while (true) {
const interaction = await client.interactions.get(initialInteraction.id);
if (interaction.status === "completed") {
console.log(interaction.outputs[interaction.outputs.length - 1].text);
break;
} else if (["failed", "cancelled"].includes(interaction.status)) {
console.log(`Failed: ${interaction.status}`);
break;
}
await new Promise(resolve => setTimeout(resolve, 10000));
}
from google import genai
client = genai.Client()
stream = client.interactionsPrerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Keeps context tight: gemini-interactions-api is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for gemini-interactions-api matched our evaluation — installs cleanly and behaves as described in the markdown.
gemini-interactions-api has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in gemini-interactions-api — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend gemini-interactions-api for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
gemini-interactions-api reduced setup friction for our internal harness; good balance of opinion and flexibility.
gemini-interactions-api has been reliable in day-to-day use. Documentation quality is above average for community skills.
gemini-interactions-api reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend gemini-interactions-api for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
gemini-interactions-api is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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