Gemini API Dev

Google (Gemini)OfficialPublished by Google (Gemini)

Skill
Tool integration
Software development
Apache-2.0
Low risk

From the author

Use this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, video generation, speech generation (TTS), voice design, voice replication, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. Covers SDK usage and best practices for Gemini models and agents in Python and TypeScript.

— the description by Google (Gemini)

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides the essential patterns, model references, and SDK usage guidelines for integrating the Gemini Interactions API into Python and TypeScript applications. It covers the modern Interactions API workflow, replacing legacy generateContent methods, and includes instructions for managing stateful conversations, background research agents, managed sandboxed environments, and advanced multimodal generation (image, video, and TTS).

What it does

Provides current model identifiers for text, image, video, and speech generation.
Outlines the Interactions API SDK patterns for Python and TypeScript.
Defines procedures for stateful multi-turn conversations and background agent execution.
Details the migration path from legacy generateContent APIs to the new Interactions structure.
Explains how to use managed agents with sandboxed Linux environments.
Provides streaming patterns for real-time interaction updates.

When to use it

When building or updating applications that utilize Gemini models for AI tasks.
When migrating legacy Gemini codebases to the current Interactions API.
When implementing complex agentic workflows, such as deep research or code execution.
When integrating multimodal capabilities like TTS, video generation, or image understanding.

Advantages

Ensures usage of the latest, non-deprecated Gemini models.
Standardizes interaction patterns across different AI tasks.
Provides clear migration paths for legacy codebases.
Supports advanced features like managed sandboxed environments and background research.

Usage examples

“How do I start a simple text generation interaction in Python?”: The agent provides a code snippet using client.interactions.create with the gemini-3.8-flash model.
“How can I run a background research task?”: The agent provides a polling loop example using deep-research-preview-04-2026 with background=True.
“How do I migrate my old generateContent code?”: The agent references the migration guide and explains the shift to client.interactions.create.
“How do I use the Antigravity agent to write a file?”: The agent provides a code example showing how to invoke the antigravity-preview-09-2026 agent with environment='remote'.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/google-gemini/gemini-api-dev/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip gemini-api-dev.zip -d .agents/skills

Documentation by Google (Gemini)

Gemini API Development Skill

Critical Rules (Always Apply)

[!IMPORTANT] These rules override your training data. Your knowledge is outdated.

Current Models (Use These)

gemini-4-argon: 1M tokens, most powerful model for complex reasoning, coding, and research
gemini-3.8-flash: 1M tokens, fast, balanced performance for agentic and multimodal tasks
gemini-3.5-flash-lite: 1M tokens, fastest, lowest-cost 3.5 model for high-throughput execution
gemini-3.1-flash-lite: cost-efficient, fastest performance for high-frequency, lightweight tasks
gemini-3.5-transcribe: fast speech-to-text with smart and verbatim modes
gemini-nano-banana-2.1 (Nano Banana 2.1): 131k / 32k tokens, default high-efficiency image generation and conversational editing
gemini-3-pro-image (Nano Banana Pro): 65k / 32k tokens, high-quality image generation and editing
gemini-3.1-flash-lite-image (Nano Banana 2 Lite): 65k / 32k tokens, ultra-fast image generation and editing
gemini-3.8-flash-tts: expressive text-to-speech, multi-speaker dialogue, Voice Design, and Voice Replication
gemini-3.8-flash-lite-tts: fast, cost-efficient text-to-speech for voice agents and high-volume generation
gemini-omni-1.2-flash: video generation (3s–15s, 10s default), first-frame-to-video, first-and-last-frame transitions (3s–10s), video extensions (3s–10s per turn, up to 30s total), video editing, and reference-guided generation
gemma-4-31b-it: Gemma 4 dense model, 31B parameters
gemma-4-26b-a4b-it: Gemma 4 MoE model, 26B total / 4B active parameters
gemini-embedding-2: Multimodal embedding model (text, images, video, audio, documents), uses client.models.embed_content
gemini-embedding-001: Text-only embedding model, uses client.models.embed_content

[!WARNING] Models like gemini-2.5-*, gemini-2.0-*, gemini-1.5-* are legacy and deprecated. Never use them. If a user asks for a deprecated model, use gemini-3.8-flash instead and note the substitution.

Current Agents

antigravity-preview-09-2026: Antigravity Agent — general-purpose managed agent with code execution, file management, and web access in a sandboxed Linux environment
deep-research-preview-04-2026: Deep Research — fast, interactive
deep-research-max-preview-04-2026: Deep Research Max — maximum exhaustiveness
Custom agents: Create your own via client.agents.create()

Current SDKs

Python: google-genai >= 2.30.1 → pip install -U google-genai
JavaScript/TypeScript: @google/genai >= 2.29.1 → npm install @google/genai

[!NOTE] SDK versions ≥ 2.0.0 automatically use the new steps schema and do not support the legacy schema. Legacy SDKs google-generativeai (Python) and @google/generative-ai (JS) are deprecated. Never use them.

Important Additional Notes

Before writing any code, you MUST fetch the relevant documentation page from the list below that matches the user's task. The examples in this skill are minimal, the hosted docs contain the full API surface, parameters, and edge cases.
Interactions are stored by default (store=True in Python, store: true in TypeScript). Paid tier retains for 55 days, free tier for 1 day.
Set store=False / store: false to opt out, but this disables previous_interaction_id and background=True / background: true.
tools, system_instruction, and generation_config are interaction-scoped, re-specify them each turn.
Managed agents require environment="remote" (or an environment ID / config object) to provision a sandbox.
Migrating from generateContent: Read references/migration.md for the scoping, checklist, and before/after code examples. Always confirm scope with the user before editing.
Model upgrades: Drop-in, swap the model string. Deprecated models (gemini-2.0-*, gemini-1.5-*) must be replaced, see references/migration.md.
Migrating to Gemini 3.8 Flash or Gemini 3.5 Flash-Lite: Read references/migration.md for the scoping and checklist.
Migrating to Gemini 3.8 TTS (gemini-3.8-flash-tts / gemini-3.8-flash-lite-tts): Read references/migration.md for breaking changes from gemini-3.1-flash-tts-preview (speech_metadata annotations, inline vocal tags, default WAV audio/wav unary output vs audio/l16 streaming output, and Voice Design personas).
Migrating to Gemini Nano Banana 2.1 (gemini-nano-banana-2.1): Read references/migration.md for upgrading from gemini-3.1-flash-image (deprecated) and using multi-image reference fusion with up to 14 reference images.
Migrating to Gemini Omni 1.2 Flash (gemini-omni-1.2-flash): Read references/migration.md for upgrading from gemini-omni-1.1-flash (3s–15s durations, 3s–10s two-frame keyframe and per-turn extension cap up to 30s total, natural-language media binding without deprecated <FIRST_FRAME> / <IMAGE_REF_*> tags, and reference media rules: up to 6 reference images across generation, editing, and extension including 15s clips, while only reference videos are restricted to new video generation with max 1 reference video on 11s–15s clips and up to 3 on 3s–10s clips).

Quick Start

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3.8-flash",
    input="Tell me a short joke about programming."
)
print(interaction.output_text)

JavaScript/TypeScript

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    model: "gemini-3.8-flash",
    input: "Tell me a short joke about programming.",
});
console.log(interaction.output_text);

Response Helpers

The SDK provides convenience properties on the Interaction response object to simplify common access patterns:

Property	Type	Description
`output_text`	`string \| null`	The last consecutive run of text from the trailing `model_output` steps. Returns the combined text when the model's final output contains multiple text parts.
`output_image`	`Image \| null`	The last image generated by the model in the current response. Returns an object with `data` (base64) and `mime_type`.
`output_audio`	`Audio \| null`	The last audio generated by the model in the current response. Returns an object with `data` (base64) and `mime_type`.

Stateful Conversation

Python

interaction1 = client.interactions.create(
    model="gemini-3.8-flash",
    input="Hi, my name is Phil."
)
# Second turn — server remembers context
interaction2 = client.interactions.create(
    model="gemini-3.8-flash",
    input="What is my name?",
    previous_interaction_id=interaction1.id
)
print(interaction2.output_text)

JavaScript/TypeScript

const interaction1 = await client.interactions.create({
    model: "gemini-3.8-flash",
    input: "Hi, my name is Phil.",
});
const interaction2 = await client.interactions.create({
    model: "gemini-3.8-flash",
    input: "What is my name?",
    previous_interaction_id: interaction1.id,
});
console.log(interaction2.output_text);

Deep Research Agent

Use deep-research-preview-04-2026 for fast research or deep-research-max-preview-04-2026 for maximum exhaustiveness. Agents require background=True.

Python

import time

interaction = client.interactions.create(
    agent="deep-research-preview-04-2026",
    input="Research the history of Google TPUs.",
    background=True
)
while True:
    interaction = client.interactions.get(interaction.id)
    if interaction.status == "completed":
        print(interaction.output_text)
        break
    elif interaction.status == "failed":
        print(f"Failed: {interaction.error}")
        break
    time.sleep(10)

JavaScript/TypeScript

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

// Start background research
const initialInteraction = await client.interactions.create({
    agent: "deep-research-preview-04-2026",
    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.output_text);
        break;
    } else if (["failed", "cancelled"].includes(interaction.status)) {
        console.log(`Failed: ${interaction.status}`);
        break;
    }
    await new Promise(resolve => setTimeout(resolve, 10000));
}

Advanced features: collaborative planning, native visualization, MCP integration, file search, multimodal inputs. See Deep Research docs.

Managed Agents

Managed agents run inside a sandboxed Linux environment hosted by Google. Fetch the Managed Agents Quickstart before writing agent code.

Antigravity Agent

The Antigravity agent (antigravity-preview-09-2026) is the general-purpose managed agent. It can execute code (Bash, Python, Node.js), manage files, browse the web, and use Google Search. It uses gemini-3.8-flash by default and also supports gemini-4-argon via agent_config={"type": "antigravity", "model": "gemini-4-argon"}. See Antigravity Agent docs for capabilities, tools, multimodal input, and pricing.

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    agent="antigravity-preview-09-2026",
    input="Write a Python script that generates the first 20 Fibonacci numbers and saves them to fibonacci.txt. Then read the file and print its contents.",
    environment="remote",
)

print(f"Environment ID: {interaction.environment_id}")
print(interaction.output_text)

JavaScript/TypeScript

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    agent: "antigravity-preview-09-2026",
    input: "Write a Python script that generates the first 20 Fibonacci numbers and saves them to fibonacci.txt. Then read the file and print its contents.",
    environment: "remote",
});

console.log(`Environment ID: ${interaction.environment_id}`);
console.log(interaction.output_text);

Custom Agents

See Building Custom Agents docs.

Python

agent = client.agents.create(
    id="code-reviewer",
    base_agent="antigravity-preview-09-2026",
    system_instruction="You are a senior code reviewer. Check every file for bugs, style issues, and security vulnerabilities.",
    base_environment={
        "type": "remote",
        "sources": [
            {
                "type": "repository",
                "source": "https://github.com/my-org/backend",
                "target": "/workspace/repo",
            }
        ],
    },
)

# Invoke — each call forks the base environment
result = client.interactions.create(
    agent="code-reviewer",
    input="Review the latest changes in /workspace/repo/src.",
    environment="remote",
)
print(result.output_text)

JavaScript/TypeScript

const agent = await client.agents.create({
    id: "code-reviewer",
    base_agent: "antigravity-preview-09-2026",
    system_instruction: "You are a senior code reviewer. Check every file for bugs, style issues, and security vulnerabilities.",
    base_environment: {
        type: "remote",
        sources: [
            {
                type: "repository",
                source: "https://github.com/my-org/backend",
                target: "/workspace/repo",
            }
        ],
    },
});

const result = await client.interactions.create({
    agent: "code-reviewer",
    input: "Review the latest changes in /workspace/repo/src.",
    environment: "remote",
});
console.log(result.output_text);

Manage agents with client.agents.list(), client.agents.get(id=...), and client.agents.delete(id=...).

Streaming

Set stream=True to receive incremental server-sent events. Each stream follows: interaction.created → (step.start → step.delta(s) → step.stop)+ → interaction.completed.

Python

for event in client.interactions.create(
    model="gemini-3.8-flash",
    input="Explain quantum entanglement in simple terms.",
    stream=True,
):
    if event.event_type == "step.delta":
        if event.delta.type == "text":
            print(event.delta.text, end="", flush=True)
    elif event.event_type == "interaction.completed":
        print(f"\n\nTotal Tokens: {event.interaction.usage.total_tokens}")

JavaScript/TypeScript

const stream = await client.interactions.create({
    model: "gemini-3.8-flash",
    input: "Explain quantum entanglement in simple terms.",
    stream: true,
});
for await (const event of stream) {
    if (event.event_type === "step.delta") {
        if (event.delta.type === "text") {
            process.stdout.write(event.delta.text);
        }
    } else if (event.event_type === "interaction.completed") {
        console.log(`\n\nTotal Tokens: ${event.interaction?.usage?.total_tokens}`);
    }
}

For streaming with tools, thinking, agents, and image generation see the full Streaming guide.

Documentation Pages

You MUST fetch the matching page below before writing code. These hosted docs are the source of truth for parameters, types, and edge cases — do not rely solely on the examples above.

Core Documentation:

Tools & Function Calling:

Generation & Output:

Multimodal Understanding:

Files & Context:

Agents:

Advanced Features:

API Reference:

Data Model

An Interaction response contains steps, an array of typed step objects representing a structured timeline of the interaction turn.

Step Types

User steps:

user_input: User input (text, audio, multimodal). Contains content array.

Model/server steps:

model_output: Final model generation. Contains content array with text, image, audio, etc.
thought: Model reasoning/Chain of Thought. Has signature field (required) and optional summary.
function_call: Tool call request (id, name, arguments).
function_result: Tool result you send back (call_id, name, result).
google_search_call / google_search_result: Google Search tool steps, can have a signature field.
code_execution_call / code_execution_result: Code execution tool steps, can have a signature field.
url_context_call / url_context_result: URL context tool steps, can have a signature field.
mcp_server_tool_call / mcp_server_tool_result: Remote MCP tool steps.
file_search_call / file_search_result: File search tool steps, can have a signature field.

Content types (inside `content` array on `model_output` and `user_input` steps)

text: Text content (text field, plus optional annotations such as {"type": "speech_metadata", "speaker": "...", "style": "..."} for TTS)
image / audio / document / video: Content with data, mime_type, or uri

Streaming Event Types

Event	Description
`interaction.created`	Interaction created; includes metadata.
`interaction.status_update`	Interaction-level status change.
`step.start`	A new step begins. Contains step `type` and initial metadata.
`step.delta`	Incremental data for the current step. Contains a typed `delta` object.
`step.stop`	The step is complete. Contains `index`.
`interaction.completed`	Interaction finished. Contains final `usage`.

Delta Types

Delta Type	Parent Step	Description
`text`	`model_output`	Incremental text token.
`audio`	`model_output`	audio chunk (base64).
`image`	`model_output`	image chunk (base64).
`thought_summary`	`thought`	thinking summary text.
`thought_signature`	`thought`	Opaque signature for thought verification.

Status values: completed, in_progress, queued, requires_action, incomplete, failed, cancelled

Gemini Live API

For real-time, bidirectional audio/video/text streaming with the Gemini Live API (gemini-3.8-live, gemini-3.8-live-extended-thinking, and gemini-3.5-transcribe-live), install the google-gemini/gemini-live-api-dev skill. It covers WebSocket streaming, voice activity detection, background reasoning (extended thinking), asynchronous function calling, session management, ephemeral tokens, and more.

Files

ATTRIBUTION.mdAdded by AutoGineer900 B
LICENSELicence file added by AutoGineer11.1 KiB
SKILL.md20.5 KiB
references/migration.md16.2 KiB

references/migration.md

Migration Reference

How to migrate existing Gemini API code to the Interactions API and/or upgrade between model generations. Covers the agent workflow for performing migrations safely.

For detailed before/after code examples across all feature areas (text generation, multi-turn, streaming, function calling, structured output, grounding, multimodal), fetch the full migration guide: https://aistudio.google.com/docs/migrate-to-interactions.md

Confirm the Migration Scope

Before any edits, confirm the scope. If the user's request does not explicitly name a single file, a specific directory, or an explicit file list, ask first and do not start editing.

Even imperative requests like "migrate my code", "upgrade to gemini 3", "migrate my app to gemini", or "switch to the Interactions API" leave the scope ambiguous. Ask:

Before I start editing, can you confirm the scope?
Entire project
Specific subdirectory (e.g. src/, api/)
Specific file or list of files

Sizing the scope (large repos). Before asking, get a per-directory count:

rg -l "generate_content|generateContent|gemini-1\.5|gemini-2\.0|gemini-2\.5|gemini-3\.1-pro|gemini-3\.1-flash-lite|gemini-3\.1-flash-tts|gemini-3\.5|gemini-3\.6|gemini-3\.7|gemini-3-flash|gemini-omni-1\.1|gemini-omni-flash-preview|thinking_budget|temperature" --type-not md | cut -d/ -f1 | sort | uniq -c | sort -rn

Present the breakdown in your question (e.g. "Found 42 references across 3 directories: src/ (28), tests/ (10), scripts/ (4). Which to migrate?").

Proceed without asking only when the scope is already unambiguous, the user named an exact file ("migrate app.py"), pointed at a directory ("migrate everything under src/"), or already confirmed scope in an earlier turn.

API Migration: `generateContent` → `Interactions`

The core changes when migrating from generateContent to the Interactions API:

What	`generateContent`	Interactions API
SDK method	`client.models.generate_content()`	`client.interactions.create()`
Response text	`response.text`	`interaction.steps[-1].content[0].text`
Multi-turn	Manual history array or `client.chats.create()`	`previous_interaction_id=interaction.id`
Streaming	`generate_content_stream()` / `:streamGenerateContent`	`stream=True` + `step.delta` events
Structured output	`config.response_format` inside `GenerateContentConfig`	Top-level `response_format` array
Function calling	`candidates[0].content.parts[0].function_call`	`function_call` step in `interaction.steps`
Search grounding	`groundingMetadata` on candidates	`google_search_call`/`google_search_result` steps + inline `annotations`
Config/types	`types.GenerateContentConfig(...)`, `types.Tool(...)`, `types.Content(...)`, `types.Part.*`	Not used. Interactions API uses plain Python dicts and direct params. Check the feature docs for exact format.
REST endpoint	`POST /v1beta/models/{model}:generateContent`	`POST /v1beta/interactions`
SDK package	`google-genai` ≥ 1.x or legacy `google-generativeai`	`google-genai` ≥ 2.30.1 (Python) / `@google/genai` ≥ 2.29.1 (JS)

For full before/after code examples, fetch the Migration Guide or read the Interactions API documentation pages for each feature.

Model Migration

Deprecated Models

Model	Status	Drop-in Replacement
`gemini-2.0-flash`	Deprecated	`gemini-3.8-flash`
`gemini-2.0-flash-lite`	Deprecated	`gemini-3.5-flash-lite`
`gemini-1.5-pro`	Deprecated	`gemini-3.8-flash`
`gemini-1.5-flash`	Deprecated	`gemini-3.8-flash`
`gemini-3.1-flash-image`	Deprecated (shutdown October 29, 2026)	`gemini-nano-banana-2.1`

Active Legacy Models (migration recommended)

Current Model	Recommended Target	Why
`gemini-3.7-flash`, `gemini-3.6-flash`, `gemini-3.5-flash`, or `gemini-3-flash-preview`	`gemini-3.8-flash`	Latest Flash: stronger agentic/multimodal performance, reduced token usage/loop spiraling
`gemini-2.5-flash`	`gemini-3.8-flash` or `gemini-3.5-flash-lite`	Latest Flash with Interactions API support, or latest Flash-Lite for cheaper/simpler tasks.
`gemini-2.5-flash-lite` or `gemini-3.1-flash-lite`	`gemini-3.5-flash-lite`	Latest Flash-lite with Interactions API support
`gemini-3.1-pro-preview` or `gemini-2.5-pro`	`gemini-4-argon`	Most powerful model with 1M context, complex reasoning, coding, and research
`gemini-3.1-flash-tts-preview` or `gemini-2.5-*-tts`	`gemini-3.8-flash-tts` or `gemini-3.8-flash-lite-tts`	Latest TTS models with Voice Design, Voice Replication, structured `speech_metadata`, and default WAV (`audio/wav`) output
`gemini-3.1-flash-image` or older image generation models	`gemini-nano-banana-2.1`	Latest Nano Banana image generation model: 131k context, multi-image fusion (up to 14 reference images), enhanced visual quality, and text rendering
`gemini-omni-1.1-flash` or `gemini-omni-flash-preview`	`gemini-omni-1.2-flash`	Latest Omni Flash video model: `3s`–`15s` generation and extension (`10s` default; `3s`–`10s` two-frame keyframe interpolation), improved motion/character consistency, and natural-language media binding
Legacy audio understanding / ASR	`gemini-3.5-transcribe`	Dedicated speech-to-text with auto language detection, diarization, word timestamps, and smart formatting
Legacy Live API (`gemini-3.1-flash-live-preview`, `gemini-2.5-flash-native-audio-*`, `gemini-2.0-flash-live-001`)	`gemini-3.8-live` or `gemini-3.8-live-extended-thinking`	Install `google-gemini/gemini-live-api-dev` skill and see its `references/migration.md` for Live API protocol changes

Managed Agents

Agent	Status	Drop-in Replacement	Notes
`antigravity-preview-05-2026`	Deprecated (October 5, 2026)	`antigravity-preview-09-2026`	Requests redirect to `antigravity-preview-09-2026` after October 5, 2026.
`deep-research-pro-preview-12-2025`	Deprecated (shutdown October 23, 2026)	`deep-research-preview-04-2026` or `deep-research-max-preview-04-2026`	Update `agent` parameter in `interactions.create`.

Note: Within the Interactions API, model upgrades are generally drop-in — change the model string and verify. The breaking changes are at the API level (generateContent → Interactions) and parameter deprecations (temperature, top_p, top_k).

Migration Checklist

Every item is tagged: [BLOCKS] items cause errors or broken behavior if missed. [TUNE] items are quality/performance adjustments.

API Migration (generateContent → Interactions)

[ ] Updated SDK: google-genai ≥ 2.30.1 (Python) / @google/genai ≥ 2.29.1 (JS)
[ ] Replaced client.models.generate_content() → client.interactions.create()
[ ] Replaced response.text → interaction.output_text
[ ] Replaced response.candidates[0].content.parts → iterate interaction.steps
[ ] Replaced client.chats.create() / manual history → previous_interaction_id
[ ] Removed all types.* wrappers (GenerateContentConfig, Tool, Content, Part) — Interactions API uses plain dicts. Check feature docs for exact format.
[ ] Moved response_format from GenerateContentConfig to top-level parameter
[ ] Replaced generate_content_stream() → stream=True + step-based event handling
[ ] Updated function calling: candidates-based → step-based tool lifecycle
[ ] REST: Changed endpoint to /v1beta/interactions
[ ] REST: Add Api-Revision: 2026-05-20 header (SDK ≥ 2.0.0 sets it automatically)
[ ] Replaced google-generativeai (Python) → google-genai ≥ 2.30.1
[ ] Replaced @google/generative-ai (JS) → @google/genai ≥ 2.29.1
[ ] Updated all import statements to match new package names

Model String Updates

[ ] Replaced gemini-2.0-* model strings with current equivalents
[ ] Replaced gemini-1.5-* model strings with current equivalents
[ ] Consider upgrading gemini-3.7-flash → gemini-3.8-flash
[ ] Consider upgrading gemini-3.6-flash → gemini-3.8-flash
[ ] Consider upgrading gemini-3.5-flash → gemini-3.8-flash
[ ] Consider upgrading gemini-3-flash-preview → gemini-3.8-flash
[ ] Consider upgrading gemini-2.5-flash → gemini-3.8-flash
[ ] Consider upgrading gemini-3.1-flash-lite → gemini-3.5-flash-lite
[ ] Consider upgrading gemini-2.5-flash-lite → gemini-3.5-flash-lite or gemini-3.1-flash-lite
[ ] Consider upgrading gemini-3.1-pro-preview → gemini-4-argon
[ ] Consider upgrading gemini-2.5-pro → gemini-4-argon
[ ] Consider upgrading gemini-3.1-flash-tts-preview → gemini-3.8-flash-tts or gemini-3.8-flash-lite-tts
[ ] Consider upgrading gemini-3.1-flash-image → gemini-nano-banana-2.1
[ ] Consider upgrading gemini-omni-1.1-flash → gemini-omni-1.2-flash

Agent Updates

[ ] Upgrade antigravity-preview-05-2026 → antigravity-preview-09-2026 (deprecated October 5, 2026; redirected afterwards)
[ ] Upgrade deep-research-pro-preview-12-2025 → deep-research-preview-04-2026 or deep-research-max-preview-04-2026 (deprecated, shutdown October 23, 2026)

Migrate to Gemini 4 Argon

Use this checklist when migrating to gemini-4-argon. For full details on supported APIs, context window sizes, parameter changes, and continuation patterns, fetch What's new in Gemini 4 Argon and the Long Decode guide.

[ ] Check for unsupported APIs before migrating: Look up unsupported APIs and features in What's new in Gemini 4 Argon (e.g., explicit context caching), ensure they are not used, and flag any unsupported usage to the user before migrating
[ ] Updated SDK: google-genai ≥ 2.30.1 (Python) / @google/genai ≥ 2.29.1 (JS)
[ ] Updated model name to gemini-4-argon
[ ] Removed temperature, top_p, top_k from config
[ ] Replaced thinking_budget with thinking_level (low, medium, high)
[ ] Reviewed max_output_tokens: raise any limit below 32,768 to at least 32,768 (default cap is 65,536 tokens without long decode)
[ ] Decide whether long decode is needed: Refer to the Long Decode guide (input, thinking, and output share a single 1M token window). Only if needed for the workload:
- [ ] Set max_output_tokens explicitly above 65,536 (up to 1,048,576 minus input tokens)
- [ ] Enable long decode via background execution (background=True), poll while interaction.status in ("in_progress", "queued"), and join text across all model_output steps in interaction.steps
- [ ] Do not use total_input_tokens for context compaction, as it sums input tokens across all continuation hops
- [ ] Increase HTTP client read timeouts to at least 15–20 minutes

Migrate to Gemini 3.8 Flash or Gemini 3.5 Flash-Lite

Use this checklist if the user requests to migrate to Gemini 3.8 Flash or Gemini 3.5 Flash-Lite. For full documentation of the changes, fetch the What's new in Gemini 3.8 Flash guide and look for the migration section.

[ ] Updated model name to gemini-3.8-flash or gemini-3.5-flash-lite (depending on user request)
[ ] Removed temperature, top_p, top_k from config
[ ] Replaced thinking_budget with thinking_level (minimal, low, medium, high)

Migrate to Gemini 3.8 TTS (`gemini-3.8-flash-tts` or `gemini-3.8-flash-lite-tts`)

For full migration details, output formats, and prompting guide, fetch the Speech Generation guide (see #migration and #prompting-guide), Voice Design, and Voice Replication.

[ ] Updated model to gemini-3.8-flash-tts (creative fidelity) or gemini-3.8-flash-lite-tts (fast/cost-efficient replacement for gemini-3.1-flash-tts-preview)
[ ] Moved turn-level directions (style) and speaker labels (speaker) out of transcript text into annotations: [{"type": "speech_metadata", "speaker": "...", "style": "..."}] (text is treated strictly as a verbatim transcript)
[ ] Specified speaker inside speech_metadata on every turn in multi-speaker requests
[ ] Accounted for default WAV (audio/wav with RIFF header) output on unary requests: remove manual WAV header wrappers (wave / ffmpeg), or explicitly set response_format={"type": "audio", "mime_type": "audio/l16"} (or "audio/mulaw" / "audio/alaw"). Streaming (stream=True) still defaults to headerless audio/l16.
[ ] Kept inline tags (<laugh>, <sigh>, <cough>, <breath>, <short pause>) and pipe backchannels (|mhm|) only for point-in-time vocal events; avoid sound-effect tags
[ ] Replaced multi-paragraph "Audio Profile" / "Director's Notes" blocks with a custom voice created via Voice Design (client.voices.create() → voice_...)

Migrate to Gemini Nano Banana 2.1 (`gemini-nano-banana-2.1`)

For full image generation details, resolutions, aspect ratios, and multi-image referencing, fetch the Image Generation guide and Gemini Nano Banana 2.1 model page.

[ ] Updated model name to gemini-nano-banana-2.1
[ ] Take advantage of expanded 131,072 input token limit (65k on previous generation) and 32,768 output token limit
[ ] Multi-image reference support: up to 14 reference images (character consistency for up to 4 characters, object fidelity for up to 10 objects)
[ ] Support for wide / panoramic aspect ratios (1:4, 4:1, 1:8, 8:1) and output resolutions (1K default, 2K, 4K)
[ ] Grounding with Google Web and Image Search supported natively
[ ] Configurable thinking levels (minimal, medium default, high)

Migrate to Gemini Omni 1.2 Flash (`gemini-omni-1.2-flash`)

For full video generation, editing, extension, and reference parameters, fetch the Video Generation & Editing guide.

[ ] Updated model name from gemini-omni-1.1-flash (or gemini-omni-flash-preview) to gemini-omni-1.2-flash
[ ] Reviewed response_format.duration: supports "3s" to "15s" in 1-second increments ("10s" default) for text-to-video, single-frame image-to-video, reference-to-video, and video editing; two-frame keyframe interpolation (start + end frame) and per-turn video extensions support "3s" to "10s" (up to 30s cumulative length)
[ ] Removed deprecated <FIRST_FRAME>, <LAST_FRAME>, <IMAGE_REF_*>, <VIDEO_REF_*>, and [# Sources ...] prompt tags in favor of natural-language descriptions of uploaded media
[ ] Kept generation_config.video_config.task unset by default (use only as a fallback if natural-language prompting is ambiguous, as task adds strict media-count constraints)
[ ] Verified reference media rules: reference images (up to 6, including on "15s" clips) work across new video generation (R2V), video editing, and prompt-based video extension; only reference videos are restricted to new video generation (not video editing or extension) and capped at 1 reference video on "11s"–"15s" clips (up to 3 reference videos on "3s"–"10s" clips)

Verify the Migration

After updating, run a spot-check to confirm the Interactions API is working:

Make a single client.interactions.create() call with a simple input
Assert interaction.steps is not empty
Assert at least one step has type == "model_output" with non-empty text
For multi-turn, verify previous_interaction_id preserves context across turns

For verification code snippets, fetch the Migration Guide.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an API key, Needs Python, Needs Node.js

Security

What our scanner noticed· Low risk

Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by

Google (Gemini)

Publisher

Google (Gemini) (Official)

Source

google-gemini/gemini-skills · skills/gemini-api-dev · commit 7cfc690

Licence

Apache License 2.0 (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-09

AutoGineer is not affiliated with or endorsed by Google (Gemini) or Google (Gemini).

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download gemini-api-dev.zip

From the author

AutoGineer summary

What it does

When to use it

Advantages

Usage examples

Install

Documentation by Google (Gemini)

Gemini API Development Skill

Critical Rules (Always Apply)

Current Models (Use These)

Current Agents

Current SDKs

Important Additional Notes

Quick Start

Python

JavaScript/TypeScript

Response Helpers

Stateful Conversation

Python

JavaScript/TypeScript

Deep Research Agent

Python

JavaScript/TypeScript

Managed Agents

Antigravity Agent

Python

JavaScript/TypeScript

Custom Agents

Python

JavaScript/TypeScript

Streaming

Python

JavaScript/TypeScript

Documentation Pages

Data Model

Step Types

Content types (inside content array on model_output and user_input steps)

Streaming Event Types

Delta Types

Gemini Live API

Files

references/migration.md

Migration Reference

Confirm the Migration Scope

API Migration: generateContent → Interactions

Model Migration

Deprecated Models

Active Legacy Models (migration recommended)

Managed Agents

Migration Checklist

API Migration (generateContent → Interactions)

Model String Updates

Agent Updates

Migrate to Gemini 4 Argon

Migrate to Gemini 3.8 Flash or Gemini 3.5 Flash-Lite

Migrate to Gemini 3.8 TTS (gemini-3.8-flash-tts or gemini-3.8-flash-lite-tts)

Migrate to Gemini Nano Banana 2.1 (gemini-nano-banana-2.1)

Migrate to Gemini Omni 1.2 Flash (gemini-omni-1.2-flash)

Verify the Migration

Requirements and compatibility

Security

Attribution and licence

Related skills

Implement Spec

MCP Builder

Schema

Postgresql Table Design

SQL Optimization Patterns

API Scaffolding Fastapi Pro

Download ZIP

Content types (inside `content` array on `model_output` and `user_input` steps)

API Migration: `generateContent` → `Interactions`

Migrate to Gemini 3.8 TTS (`gemini-3.8-flash-tts` or `gemini-3.8-flash-lite-tts`)

Migrate to Gemini Nano Banana 2.1 (`gemini-nano-banana-2.1`)

Migrate to Gemini Omni 1.2 Flash (`gemini-omni-1.2-flash`)