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Gemini Omni Flash Skill · sickn33 | DecimalAI

Design & Mediaby sickn33

Gemini Omni Flash Skill

Use this skill for generative video editing, text-to-video, image-referenced video generation, and first-frame-to-video transition animations using the official google-genai SDK. Includes workflows for pre-processing/optimizing high-resolution or long source videos with ffmpeg,...

Never made a case worseMaintained

SkillScore

SkillScore91/100

Test results 91

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

18%91%of test cases passed +73 pts

Without skill4 of 22

With skill20 of 22

16 fixed4 passed either way2 still failing0 broke

Measured on gemini-3.6-flash8/8/2026v1 · latest is v221 comparable

This benchmark measured an earlier version of the skill.

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskI generated a video earlier and received interaction ID `int_89f23a`. I want to edit this existing generation to change the setting to a snowy winter landscape without re-uploading the original source video. How do I request this edit?

Without the skillMissed

With the skillPassed

Same model, same task. Answers are capped and redacted.

Use this skill

Your agent runs on

Adds every file the skill has, pinned so you can update it. No account needed.

pip install "decimalai>=0.15"
decimalai skills add sickn33-gemini-omni-flash-api
claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"

The same install from Python, for a notebook or a setup script.

Install

pip install "decimalai>=0.15"

Add the skill

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

print("Added. Start Claude Code with the command below.")

Start Claude Code with it

claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"

Type these in a Claude Code session. No account or API key. It writes the skill and any files it bundles, and asks first when its safety rating isn't Passed.

Add the DecimalAI plugin, once

/plugin marketplace add decimal-labs/decimalai-claude-plugins
/plugin install decimalai@decimalai

Install this skill

/decimalai:install sickn33-gemini-omni-flash-api

The plugin needs python3 and curl on your machine.

No Python or account. Claude Code picks it up in its next session.

Save it into your project

curl -fsSL --create-dirs -o .claude/skills/sickn33-gemini-omni-flash-api/SKILL.md https://app.decimal.ai/s/sickn33-gemini-omni-flash-api/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/sickn33-gemini-omni-flash-api/SKILL.md

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Claude Code docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"
decimalai skills add sickn33-gemini-omni-flash-api

Add it to your agent

import asyncio

from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

async def main():
    question = "Hello!"
    async with support.run(question) as run:  # one user message, one run
        async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
            print(message)

# In a notebook or async code: await main()
asyncio.run(main())

Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

import asyncio

from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

async def main():
    question = "Hello!"
    async with support.run(question) as run:  # one user message, one run
        async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
            print(message)

# In a notebook or async code: await main()
asyncio.run(main())

Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from claude_agent_sdk import ClaudeAgentOptions, query

skill = Path(".agents/skills/sickn33-gemini-omni-flash-api/SKILL.md").read_text()
options = ClaudeAgentOptions(system_prompt=f"You are a helpful agent.\n\n{skill}", max_turns=6)

async def main():
    async for message in query(prompt="Hello!", options=options):
        print(message)

# In a notebook or async code: await main()
asyncio.run(main())

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Claude Agent SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai-agents]"
decimalai skills add sickn33-gemini-omni-flash-api

Add it to your agent

from agents import Agent, Runner
from decimalai.openai_agents import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    name=support.name,
    instructions=support.instructions,  # your prompt, then the skill list
    tools=[*support.tools],             # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.

Install

pip install "decimalai[openai-agents]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

from agents import Agent, Runner
from decimalai.openai_agents import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    name=support.name,
    instructions=support.instructions,  # your prompt, then the skill list
    tools=[*support.tools],             # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/sickn33-gemini-omni-flash-api/SKILL.md").read_text()
agent = Agent(name="support", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

OpenAI Agents docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai]"
decimalai skills add sickn33-gemini-omni-flash-api

Add it to your agent

import json

from openai import OpenAI
from decimalai.openai import agent_config

client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
                   "required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    # run.system is your prompt, then the skill list.
    messages = [{"role": "system", "content": run.system}, run.message]
    while True:
        reply = client.chat.completions.create(
            model="gpt-5.4-mini",
            messages=messages,
            tools=[*TOOLS, *run.tools],  # your tools, then load_skill
        ).choices[0].message
        messages.append(reply)
        if not reply.tool_calls:
            break
        for call in reply.tool_calls:
            # load_skill is answered by the run; your own tools by FUNCTIONS.
            function = FUNCTIONS.get(call.function.name)
            messages.append(run.tool_result(call) or {
                "role": "tool", "tool_call_id": call.id,
                "content": function(**json.loads(call.function.arguments)) if function
                else f"There is no tool named {call.function.name!r}.",
            })
print(reply.content)

# The Responses API takes run.response_tools instead of run.tools.

Install

pip install "decimalai[openai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

import json

from openai import OpenAI
from decimalai.openai import agent_config

client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
                   "required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    # run.system is your prompt, then the skill list.
    messages = [{"role": "system", "content": run.system}, run.message]
    while True:
        reply = client.chat.completions.create(
            model="gpt-5.4-mini",
            messages=messages,
            tools=[*TOOLS, *run.tools],  # your tools, then load_skill
        ).choices[0].message
        messages.append(reply)
        if not reply.tool_calls:
            break
        for call in reply.tool_calls:
            # load_skill is answered by the run; your own tools by FUNCTIONS.
            function = FUNCTIONS.get(call.function.name)
            messages.append(run.tool_result(call) or {
                "role": "tool", "tool_call_id": call.id,
                "content": function(**json.loads(call.function.arguments)) if function
                else f"There is no tool named {call.function.name!r}.",
            })
print(reply.content)

# The Responses API takes run.response_tools instead of run.tools.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/sickn33-gemini-omni-flash-api/SKILL.md").read_text()
reply = client.chat.completions.create(
    model="gpt-5.4-mini",
    messages=[
        {"role": "system", "content": f"You are a helpful agent.\n\n{skill}"},
        {"role": "user", "content": "Hello!"},
    ],
).choices[0].message

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

OpenAI SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[anthropic]"
decimalai skills add sickn33-gemini-omni-flash-api

Add it to your agent

import anthropic
from decimalai.anthropic import agent_config

client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

question = "Hello!"
with support.run(question) as run:  # one user message, one run
    answer = client.beta.messages.tool_runner(
        model="claude-haiku-5-5",
        max_tokens=4096,
        system=run.system,     # your prompt, then the skill list
        tools=[*run.tools],    # your tools, then load_skill
        messages=[{"role": "user", "content": question}],
    ).until_done()

Install

pip install "decimalai[anthropic]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

import anthropic
from decimalai.anthropic import agent_config

client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

question = "Hello!"
with support.run(question) as run:  # one user message, one run
    answer = client.beta.messages.tool_runner(
        model="claude-haiku-5-5",
        max_tokens=4096,
        system=run.system,     # your prompt, then the skill list
        tools=[*run.tools],    # your tools, then load_skill
        messages=[{"role": "user", "content": question}],
    ).until_done()

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/sickn33-gemini-omni-flash-api/SKILL.md").read_text()
reply = client.messages.create(
    model="claude-haiku-5-5",
    max_tokens=4096,
    system=f"You are a helpful agent.\n\n{skill}",
    messages=[{"role": "user", "content": "Hello!"}],
)

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Anthropic docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[google-genai]"
decimalai skills add sickn33-gemini-omni-flash-api

Add it to your agent

from google import genai
from google.genai import types
from decimalai.google_genai import agent_config

client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
                               "required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    config = types.GenerateContentConfig(
        system_instruction=run.system,     # your prompt, then the skill list
        tools=[*TOOLS, *run.tool_params],  # your functions, then load_skill
    )
    contents = [{"role": "user", "parts": [{"text": run.message}]}]
    while True:
        response = client.models.generate_content(
            model="gemini-3.5-flash", contents=contents, config=config,
        )
        if not response.function_calls:
            break
        contents.append(response.candidates[0].content)
        parts = []
        for call in response.function_calls:
            # load_skill is answered by the run; your own functions by FUNCTIONS.
            # A loop of your own rather than automatic function calling, which
            # raises KeyError when the model asks for a function you did not pass.
            function = FUNCTIONS.get(call.name)
            parts.append(run.tool_result(call) or {"function_response": {
                "name": call.name, "id": call.id,
                "response": {"result": function(**(call.args or {})) if function
                             else f"There is no function named {call.name!r}."},
            }})
        contents.append({"role": "user", "parts": parts})
print(response.text)

Install

pip install "decimalai[google-genai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

from google import genai
from google.genai import types
from decimalai.google_genai import agent_config

client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
                               "required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    config = types.GenerateContentConfig(
        system_instruction=run.system,     # your prompt, then the skill list
        tools=[*TOOLS, *run.tool_params],  # your functions, then load_skill
    )
    contents = [{"role": "user", "parts": [{"text": run.message}]}]
    while True:
        response = client.models.generate_content(
            model="gemini-3.5-flash", contents=contents, config=config,
        )
        if not response.function_calls:
            break
        contents.append(response.candidates[0].content)
        parts = []
        for call in response.function_calls:
            # load_skill is answered by the run; your own functions by FUNCTIONS.
            # A loop of your own rather than automatic function calling, which
            # raises KeyError when the model asks for a function you did not pass.
            function = FUNCTIONS.get(call.name)
            parts.append(run.tool_result(call) or {"function_response": {
                "name": call.name, "id": call.id,
                "response": {"result": function(**(call.args or {})) if function
                             else f"There is no function named {call.name!r}."},
            }})
        contents.append({"role": "user", "parts": parts})
print(response.text)

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

Give it to your agent

from pathlib import Path
from google import genai
from google.genai import types

client = genai.Client()
skill = Path(".agents/skills/sickn33-gemini-omni-flash-api/SKILL.md").read_text()
response = client.models.generate_content(
    model="gemini-3.5-flash",
    contents="Hello!",
    config=types.GenerateContentConfig(system_instruction=f"You are a helpful agent.\n\n{skill}"),
)

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Gemini API docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[langchain]" langchain-openai
decimalai skills add sickn33-gemini-omni-flash-api

Add it to your agent

from langchain.agents import create_agent
from decimalai.langchain import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = create_agent(
    "openai:gpt-5.4-mini",
    tools=[],                         # your tools; the middleware adds load_skill
    middleware=[support.middleware],  # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

Install

pip install "decimalai[langchain]" langchain-openai

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

from langchain.agents import create_agent
from decimalai.langchain import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = create_agent(
    "openai:gpt-5.4-mini",
    tools=[],                         # your tools; the middleware adds load_skill
    middleware=[support.middleware],  # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/sickn33-gemini-omni-flash-api/SKILL.md").read_text()
agent = create_agent("openai:gpt-5.4-mini", tools=[], system_prompt=f"You are a helpful agent.\n\n{skill}")
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

LangChain docs

CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"
decimalai skills add sickn33-gemini-omni-flash-api

Add it to your agent

import decimalai.crewai
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                               # your own CrewAI LLM
    skills=decimalai.crewai.skills(),      # the installed folder
    tools=decimalai.crewai.skill_tools(),  # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

The same install from Python, for a notebook or a setup script. CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

import decimalai.crewai
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                               # your own CrewAI LLM
    skills=decimalai.crewai.skills(),      # the installed folder
    tools=decimalai.crewai.skill_tools(),  # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

No DecimalAI package. CrewAI's own loader reads the folder, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

Give it to your agent

from pathlib import Path
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                         # your own CrewAI LLM
    skills=[Path(".agents/skills")],
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

CrewAI docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[adk]"
decimalai skills add sickn33-gemini-omni-flash-api

Add it to your agent

from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = LlmAgent(
    name="support",          # ADK needs a Python identifier
    model="gemini-3.5-flash",
    instruction=support.instruction,  # your prompt, then the skill list
    tools=[*support.tools],           # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])

Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

Install

pip install "decimalai[adk]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = LlmAgent(
    name="support",          # ADK needs a Python identifier
    model="gemini-3.5-flash",
    instruction=support.instruction,  # your prompt, then the skill list
    tools=[*support.tools],           # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])

Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

Give it to your agent

from pathlib import Path
from google.adk.agents import LlmAgent

skill = Path(".agents/skills/sickn33-gemini-omni-flash-api/SKILL.md").read_text()
agent = LlmAgent(
    name="support",
    model="gemini-3.5-flash",
    instruction=lambda context: f"You are a helpful agent.\n\n{skill}",
)

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Google ADK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[pydantic-ai]"
decimalai skills add sickn33-gemini-omni-flash-api

Add it to your agent

from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    "openai:gpt-4o-mini",
    name=support.name,
    tools=[],                 # your tools; the capability adds load_skill
    capabilities=[support],   # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.

Install

pip install "decimalai[pydantic-ai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    "openai:gpt-4o-mini",
    name=support.name,
    tools=[],                 # your tools; the capability adds load_skill
    capabilities=[support],   # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/sickn33-gemini-omni-flash-api/SKILL.md").read_text()
agent = Agent("openai:gpt-4o-mini", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Pydantic AI docs

Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents
decimalai skills add sickn33-gemini-omni-flash-api

Add it to your agent

import decimalai.deepagents
from deepagents import create_deep_agent

agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).

The same install from Python, for a notebook or a setup script. Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

import decimalai.deepagents
from deepagents import create_deep_agent

agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/sickn33-gemini-omni-flash-api/SKILL.md").read_text()
agent = create_deep_agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Deep Agents docs

Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework
decimalai skills add sickn33-gemini-omni-flash-api

Add it to your agent

import asyncio

from agent_framework import Agent
from decimalai.agent_framework import skills

agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))

It caches skills by default, so restart the process after decimalai skills update.

The same install from Python, for a notebook or a setup script. Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

import asyncio

from agent_framework import Agent
from decimalai.agent_framework import skills

agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))

It caches skills by default, so restart the process after decimalai skills update.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/sickn33-gemini-omni-flash-api/SKILL.md").read_text()
agent = Agent(client=client, instructions=f"You are a helpful agent.\n\n{skill}")
asyncio.run(agent.run("Hello!"))

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Microsoft Agent Framework docs

Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents
decimalai skills add sickn33-gemini-omni-flash-api

Add it to your agent

from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell

agent = Agent(
    model=model,                # always pass one: the default is Amazon Bedrock
    system_prompt="You are a helpful agent.",
    tools=[file_editor, shell],
    plugins=[skills()],
)
agent("Hello!")

Strands loads an agent's skills once, so build the agent again after decimalai skills update.

The same install from Python, for a notebook or a setup script. Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("sickn33-gemini-omni-flash-api")
if result.exit_code:
    raise SystemExit(result.problems)

from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell

agent = Agent(
    model=model,                # always pass one: the default is Amazon Bedrock
    system_prompt="You are a helpful agent.",
    tools=[file_editor, shell],
    plugins=[skills()],
)
agent("Hello!")

Strands loads an agent's skills once, so build the agent again after decimalai skills update.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/sickn33-gemini-omni-flash-api/SKILL.md").read_text()
agent = Agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent("Hello!")

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Strands docs

Adds every file the skill has, pinned so you can update it. Cursor, Copilot, Cline and Warp read this folder by themselves.

pip install "decimalai>=0.15"
decimalai skills add sickn33-gemini-omni-flash-api

No Python or account. Cursor, Copilot, Cline and Warp read this folder by themselves.

Save it into your project

curl -fsSL --create-dirs -o .agents/skills/sickn33-gemini-omni-flash-api/SKILL.md https://app.decimal.ai/s/sickn33-gemini-omni-flash-api/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/sickn33-gemini-omni-flash-api/SKILL.md

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Cursor and other editors docs

Fetch the file and give its text to your model as instructions. No account or package needed.

Get the file

curl -fsSL https://app.decimal.ai/s/sickn33-gemini-omni-flash-api/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/sickn33-gemini-omni-flash-api.json

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v2 (v1 tested 8/8/2026)
Source: sickn33/antigravity-awesome-skills ↗
License: MIT

Manage it in DecimalAI

Saved prompts and skills, pinned versions, and traces of this skill in your runs. DecimalAI does not run your agent.

Claude Code reads files from your project, so DecimalAI config does not apply there.

On Claude Agent SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI Agents: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Anthropic: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Gemini API: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On LangChain: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On CrewAI: set DECIMAL_API_KEY and add decimalai.init(crewai=True) to record runs and skill use. The skill version stays in your repo.

On Google ADK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Pydantic AI: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Deep Agents: set DECIMAL_API_KEY and add decimalai.init(langchain=True) to record runs and skill use. The skill version stays in your repo.

On Microsoft Agent Framework: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

On Strands: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

Editors read files from your project, so DecimalAI config does not apply there.

Anywhere else: record a use with decimalai.log_skill_activation() inside a trace.

Use this skill

SKILL.md

Gemini Omni Flash Skill

When to Use

This skill uses the Gemini Omni Flash model (gemini-omni-flash-preview) to perform text to video generation, image to video generation and video editing.

[!WARNING] Important Regional Restrictions: Uploading videos to use for video edits is NOT available in the EEA, Switzerland, the United Kingdom, and some US states. If a video-to-video edit completes quickly with empty outputs (total_output_tokens: 0 or no video content), check the current availability documentation and API error; empty output alone does not identify the cause.

Core capabilities

Video editing and refinement: Editing existing videos (maximum duration 10 seconds), applying stylistic changes, or performing inpainting/outpainting.
Text to video: Generating videos from a text prompt.
First-frame to video: Generating videos from a single input image.
Image-referenced generation: Using style, character, or object references from images to guide video generation.

Data and execution boundaries

These scripts upload media and prompts to Google and can incur API charges. Confirm the selected media, remote processing and batch size are within the user request before calling. Use GEMINI_API_KEY from the environment; avoid command-line keys in shell history. Work from an isolated project directory; choose new output paths because existing files are refused. Inspect generated media and report missing or partial output honestly. Never infer a regional restriction solely from empty output; inspect API errors and current official availability. Model access, SDK version requirements, limits and pricing must be checked against official documentation before use; this static bundle does not establish them.

Workflow

Analyze request: Determine the target task (e.g., first-frame-to-video, reference-guided editing) and identify any input media assets.
Run SDK scripts:
- Directly run the appropriate utility (scripts/video/generate_video.py or scripts/upload_file.py).
- Configure settings like --aspect-ratio (e.g. 16:9, 9:16) and --duration (any integer between 3 and 10 seconds, e.g. 3, 5, 10).
Retrieve and process output: Outputs are saved to the local filesystem (e.g. media/). Report back the completed media path to the user.

Reference Documentation

Interactions API: All operations and state management for the Gemini Omni Flash model (gemini-omni-flash-preview) are handled via the Interactions API.
Files API: Input media files (such as reference images and videos) must be uploaded via the Files API first before being referenced in generations. The uploaded file URI and MIME type are then included in the interactions.create input parts array.
Interactions API Skill Reference: Platform-wide guidelines, current model specifications, and SDK usage rules for the Interactions API.

Dependencies and Prerequisites

Python SDK (google-genai): Requires google-genai >= 2.10.0 (Python) to support the new interactions client attribute. Install or upgrade using:
```
pip install -U google-genai
```
Python Runtime: Requires Python >= 3.10 (for compatibility with modern google-genai SDK types and methods).
ffmpeg & ffprobe: prep_video.py, inspect_video.py, and generate_video.py (when stripping audio via --strip-audio) require ffmpeg and ffprobe binaries installed and available in your system PATH.

Available scripts

Use the following Python scripts to upload media with the Files API, prepare input videos with ffmpeg, and generate video outputs using the Interactions API.

upload_file.py: Uploads local media (images and videos) to the Files API and polls until ACTIVE. If uploading a video larger than 25MB, it prints an informative warning/tip highlighting that Gemini Omni Flash is optimized for editing 10s videos at 720p/24fps, and recommends pre-processing with prep_video.py first to speed up the upload.
```
python3 scripts/upload_file.py path/to/image.png
```

generate_video.py: Performs end-to-end video generation and downloads the output video. It detects and uploads local media references (images or videos) before calling the Interactions API. Large video assets (>25MB) will trigger informative pre-processing recommendations without blocking the upload.

Text to video:

python3 scripts/video/generate_video.py "A close-up of a cat drinking tea" --output media/cat_tea.mp4

Image to video (first frame and reference):

python3 scripts/video/generate_video.py "The waves crash against the shore." --image reference.png --output media/waves.mp4

Video interpolation:

Provide exactly two images as keyframes to generate a transition video between them:

python3 scripts/video/generate_video.py "A smooth timelapse from sunrise to sunset" --image start.png --image end.png --output media/interpolation.mp4

Video editing (keep original audio):

python3 scripts/video/generate_video.py "Transform the style to Japanese anime" --video input.mp4 --output media/anime_style.mp4

Video editing (regenerate all audio from scratch):

python3 scripts/video/generate_video.py "Transform the style to Japanese anime" --video input.mp4 --strip-audio --output media/anime_style_new_audio.mp4

Turn-by-turn video editing (edit previous interaction):

Edit a prior video generation without re-uploading assets by passing the interaction ID:

python3 scripts/video/generate_video.py "Change the setting to a snowy winter wonderland." --previous-interaction-id "abc123xyz..." --output media/winter_wonderland.mp4

Parallel batch execution (prompts file): Run multiple prompts from a line-by-line text file concurrently:
```
python3 scripts/video/generate_video.py --prompts-file prompts.txt --concurrency 3
```

Parallel batch execution (JSON config): Execute fully configured, distinct generation and editing jobs in parallel:

python3 scripts/video/generate_video.py --batch jobs.json --concurrency 3

Example jobs.json:

[
  {
    "prompt": "Transform the style to Japanese anime.",
    "video": "input.mp4",
    "output": "media/anime_style.mp4",
    "strip_audio": false,
    "aspect_ratio": "16:9"
  },
  {
    "prompt": "A smooth timelapse from sunrise to sunset.",
    "image": ["start.png", "end.png"],
    "output": "media/interpolation.mp4"
  }
]

inspect_video.py: Inspects a local video file (using ffprobe) to check its duration, resolution, frame rate (FPS), audio stream presence, and format details.
```
python3 scripts/video/inspect_video.py media/output.mp4
```
- To get a pre-parsed, structured JSON summary:
```
python3 scripts/video/inspect_video.py media/output.mp4 --json
```
- To get the complete, unmodified ffprobe raw JSON dump:
```
python3 scripts/video/inspect_video.py media/output.mp4 --raw
```
prep_video.py: Normalizes, trims, and formats any video file to fit standard Gemini Omni Flash generation and editing limits. It handles timecode-based trimming, optional frame rate conversion, and proportional scaling of large videos (max 1280x720 for landscape, 720x1280 for portrait) to optimize upload times without stretching. If the video is longer than 10 seconds and the script is run interactively (in a TTY), it prompts the user to select the first 10s, last 10s, or enter a custom timecode (defaulting to the first 10s).
- Trim first 10s (default):
```
 python3 scripts/video/prep_video.py path/to/source.mp4
```
or explicitly specify the start and duration:
```
python3 scripts/video/prep_video.py path/to/source.mp4 --start 0 --duration 10
```
- Trim last 10s (automatically calculates starting point based on source length):
```
python3 scripts/video/prep_video.py path/to/source.mp4 --start last
```
- Trim 10s starting at specific timecode (MM:SS or HH:MM:SS):
```
python3 scripts/video/prep_video.py path/to/source.mp4 --start 00:03 --output media/custom.mp4
```
- Custom frame rate and resolution:
```
python3 scripts/video/prep_video.py path/to/source.mp4 --fps 30 --resolution 1920x1080
```
- Strip audio for audio regeneration:
```
python3 scripts/video/prep_video.py path/to/source.mp4 --strip-audio --output media/video_with_no_audio.mp4
```

Using tags in prompts to set image roles

You can use tags in your prompt to make it clear whether each uploaded media is an initial frame or a reference.

1. Simple tags (recommended)

For simple cases where image roles are clear from the prompt, you can bind images to roles directly:

<FIRST_FRAME>: Use the image as the starting frame of the video, for example: <FIRST_FRAME> a woman is walking
<IMAGE_REF_N>: Use the image as a reference, for example: in the style of <IMAGE_REF_0> a woman <IMAGE_REF_1> is walking (combines style reference from the first image and subject reference from the second image). Image references start from 0.

An example with 6 reference images:

[0-3s] A studio fashion sequence. Starting with woman <IMAGE_REF_0>, she is holding <IMAGE_REF_1>
[3-6s] Then we see the man <IMAGE_REF_2> holding <IMAGE_REF_3>
[6-10s] And finally another woman <IMAGE_REF_4> who is holding <IMAGE_REF_5> while walking.

2. Explicitly declare sources and references

For more complex cases with multiple images and multiple roles, you can use explicit prefix tags paired with natural language instruction suffixes.

Declaring sources and reference images:
- [# Sources <FIRST_FRAME>@Image1] will use the first image as the starting frame.
- [# References <IMAGE_REF_0>@Image1] will use the first image as a reference.
- [# References <IMAGE_REF_1>@Image2] will use the second image as a reference.
- [# References <IMAGE_REF_0>@Image1 <IMAGE_REF_1>@Image2] will use both images as references.
- [# Sources <FIRST_FRAME>@Image1] [# References <IMAGE_REF_0>@Image2] will use the first image as the starting frame and the second image as a reference.
Guiding instructions: Add guiding instructions at the end of your prompt:
- For starting frame: "Use the given image as the starting frame."
- For reference images: "Use the given image(s) as references for video generation. The images should not be used as literal initial frames."

Example Expanded Prompt:

[# Sources <FIRST_FRAME>@Image1] [# References <IMAGE_REF_0>@Image2] a woman <IMAGE_REF_0> is walking. Use Image1 as the starting frame. Use Image2 as a reference for the video generation.

Audio handling in video editing

When editing a source video that contains audio, you must choose between keeping the original audio or regenerating all audio from scratch.

Keep original audio: By default, Gemini Omni Flash preserves the existing audio layer (though it may modify or adapt it slightly during generation). Use this when the original background music, dialogue, or sound effects are desired.
Regenerate all audio from scratch: If you want Gemini Omni Flash to re-create a brand-new audio layer tailored to the new visual style or prompt, you must upload the video with its audio stream stripped out. If any audio stream is present, Gemini Omni Flash will attempt to preserve/modify it instead of starting from scratch.
- Use --strip-audio (or -a) when pre-processing with scripts/video/prep_video.py or executing scripts/video/generate_video.py.
- This requests a new audio track; inspect the actual output rather than assuming it is guaranteed.

Prompting Gemini Omni Flash

Single scene

By default Gemini Omni Flash will try to create a video with a few different shots. It'll attempt to craft an interesting narrative based on the prompt.

If you need the output video to contain a single scene, you must prompt for that:

In a single unbroken scene
In a single continuous shot
No scene cuts

For example:

Continuous, unbroken handheld shot of a fluffy tabby cat sitting on a sunny windowsill, looking out into a leafy garden. The cat's tail twitches slowly, and its ears rotate slightly toward ambient noises. Sunbeams illuminate dust motes in the air. Sound design: Gentle breeze, distant bird chirps, quiet mechanical purring. No dialogue.

Removing unwanted elements

If generations contain things you don't want, you can include simple negatives to avoid them:

No dialogue
No embellishments
No extra sound effects

Prompts for editing

Simple prompts work best for editing. Overly descriptive prompts can lead to unintended changes.

For example:

Make this video anime
Make the phone invisible
Put a fashionable hat on this person
Change the lighting to be more dramatic
Change the text on the sign to say "Gemini Omni Flash"
Add a cat that jumps onto his lap, he begins to pet it

When editing a specific aspect of the video, it can help to include: "Keep everything else the same".

Prompting the audio

By default the model will try to generate an appropriate audio track for a video. This might not always be what you want. You can use your prompt to describe the type of audio you want. This is especially important if you want music in your video:

Include calm background music
The video has a high energy techno beat
The audio is a low tinny radio broadcast in the background, playing a song
Audio design: [a description of the audio you want]

When things should happen

You can prompt for things to happen at specific times in the video, there is no precise syntax needed and you can use natural language. This is especially useful in creating your own scene cuts, rhythm or rapid fire sequences.

Simple examples:

after 3 seconds, a woman enters the scene
at 5s the chorus starts in the background audio
every 2s cut to a new frame
in a rapid fire sequence, every half a second (12 frames at 24fps) change the scene to a new location

You can also use a timecode syntax:

[0-3s] A person is walking
[3-6s] They stop and turn around
[6-10s] They start running

Meta prompting

Rather than specifying everything directly in a prompt, you can ask the model to pay attention to certain things. You can give Gemini Omni Flash these sorts of prompts verbatim:

Consider micro-detail, expression and timing to create a very rich, detailed but entirely natural scene.
Be extremely detailed in your descriptions of characters and environments. Apply costume design principles to characters. Be very specific about the people, items and objects in the scene.
Include plenty of appropriate detail in the background elements to make the scene feel realistic and natural.
Make a rapid fire video that shows a different rare [thing] every 1s, upbeat music, include text to label the thing.

Text in videos works really well

Unlike previous video models, text in Gemini Omni Flash videos works really well. You can include decent amounts of text in your video and it will be rendered in a way that is correct and readable. If there will be naturally occurring text in your video, even in background elements, it can help to define what it should say.

For example:

One word on the screen at a time: "did, you, know, that, Omni, can, do, awesome, text?" Each word appears for 1s with a different animated style. No dialogue.
There is a street sign that says: "This is an AI generation by Omni", there is a storefront that says: "All you need AI", there's a car with the number plate: "OMN111"

Limitations

Use this skill only when the task clearly matches its upstream product or API scope.
Verify commands, API behavior, pricing, quotas, credentials, and deployment effects against current official documentation before making changes.
Do not treat generated examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.

About this skill

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Imported

sickn33 / antigravity-awesome-skills

skills/gemini-omni-flash-api/SKILL.md

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License Apache-2.0Imported 11/8/2026Version v2Bundled 1 file · scripts

Illustrative Want to see what sickn33/gemini-omni-flash-api would put in front of your model? Preview the rendered body and check its trigger phrases — no LLM call, no signup.

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What it changes

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Use this skill

Gemini Omni Flash Skill

When to Use

Core capabilities

Data and execution boundaries

Workflow

Reference Documentation

Dependencies and Prerequisites

Available scripts

Using tags in prompts to set image roles

1. Simple tags (recommended)

2. Explicitly declare sources and references

Audio handling in video editing

Prompting Gemini Omni Flash

Single scene

Removing unwanted elements

Prompts for editing

Prompting the audio

When things should happen

Meta prompting

Text in videos works really well

Limitations

SkillSafety

Source

Related skills

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