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Neodomain AI Content Generator · leoyeai | DecimalAI

Design & Mediaby leoyeai

Neodomain AI Content Generator

Generate images and videos via Neodomain AI API. Supports text-to-image, image-to-video, text-to-video, universal multi-modal video, motion control video, and batch storyboard video generation.

Never made a case worse

SkillScore

SkillScore97/100

Test results 96 · Live runs 99

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

13%96%of test cases passed +83 pts

Without skill3 of 23

With skill22 of 23

19 fixed3 passed either way1 still failing0 broke

Measured on gemini-3.6-flash8/9/2026v1

Track record

Agent runs: 160; All time

See one task, with and without the skill

One test taskTransfer the dance motion from https://example.com/dance.mp4 onto the character in https://example.com/avatar.jpg using motion control in std mode.

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 leoyeai-neodomain-ai
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("leoyeai-neodomain-ai")
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 leoyeai-neodomain-ai

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/leoyeai-neodomain-ai/SKILL.md https://app.decimal.ai/s/leoyeai-neodomain-ai/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/leoyeai-neodomain-ai/SKILL.md

This gets SKILL.md only. The skill's 10 other files are 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 leoyeai-neodomain-ai

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("leoyeai-neodomain-ai")
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/leoyeai-neodomain-ai/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/leoyeai-neodomain-ai/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 10 other files are 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 leoyeai-neodomain-ai

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("leoyeai-neodomain-ai")
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/leoyeai-neodomain-ai/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/leoyeai-neodomain-ai/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 10 other files are 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 leoyeai-neodomain-ai

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("leoyeai-neodomain-ai")
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/leoyeai-neodomain-ai/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/leoyeai-neodomain-ai/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 10 other files are 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 leoyeai-neodomain-ai

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("leoyeai-neodomain-ai")
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/leoyeai-neodomain-ai/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/leoyeai-neodomain-ai/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 10 other files are 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 leoyeai-neodomain-ai

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("leoyeai-neodomain-ai")
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/leoyeai-neodomain-ai/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/leoyeai-neodomain-ai/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 10 other files are 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 leoyeai-neodomain-ai

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("leoyeai-neodomain-ai")
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/leoyeai-neodomain-ai/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/leoyeai-neodomain-ai/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 10 other files are 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 leoyeai-neodomain-ai

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("leoyeai-neodomain-ai")
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/leoyeai-neodomain-ai/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 10 other files are 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 leoyeai-neodomain-ai

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("leoyeai-neodomain-ai")
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/leoyeai-neodomain-ai/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/leoyeai-neodomain-ai/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 10 other files are 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 leoyeai-neodomain-ai

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("leoyeai-neodomain-ai")
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/leoyeai-neodomain-ai/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/leoyeai-neodomain-ai/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 10 other files are 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 leoyeai-neodomain-ai

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("leoyeai-neodomain-ai")
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/leoyeai-neodomain-ai/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/leoyeai-neodomain-ai/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 10 other files are 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 leoyeai-neodomain-ai

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("leoyeai-neodomain-ai")
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/leoyeai-neodomain-ai/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/leoyeai-neodomain-ai/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 10 other files are 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 leoyeai-neodomain-ai

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("leoyeai-neodomain-ai")
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/leoyeai-neodomain-ai/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/leoyeai-neodomain-ai/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 10 other files are 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 leoyeai-neodomain-ai

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/leoyeai-neodomain-ai/SKILL.md https://app.decimal.ai/s/leoyeai-neodomain-ai/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/leoyeai-neodomain-ai/SKILL.md

This gets SKILL.md only. The skill's 10 other files are 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/leoyeai-neodomain-ai/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/leoyeai-neodomain-ai.json

This gets SKILL.md only. The skill's 10 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 8/9/2026
Source: LeoYeAI/openclaw-master-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

Neodomain AI Content Generator

核心行为规范

Token 检查：每次执行前确认 NEODOMAIN_ACCESS_TOKEN 已设置。若未设置或遇到 token 过期错误（errCode 2001），立即走认证流程，动态询问用户手机号/邮箱，不要硬编码保存。
模型选择：根据用户需求按模型选择逻辑自主选择，无需询问用户（除非用户明确指定）。
提示词规范：必须遵循各模式的提示词公式，尤其是 UNIVERSAL_TO_VIDEO 必须用 @图片 1/@视频 1 等明确引用素材。
输出目录：默认使用 ./output，若用户未指定则不需询问。
--generate-audio 是布尔 flag，写 --generate-audio 即可，不要写 --generate-audio true。

⚠️ 常见问题与解决方案 (FAQ)

1. Token has been revoked (errCode 2001)

现象：视频生成 API 返回 Token has been revoked，但图片 API 可能正常。

原因：

企业版 token 的视频服务权限被撤销
Token 已过期
服务端认证系统临时故障

解决方案：

先用图片 API 测试 token 是否有效：curl -H "accessToken: $TOKEN" https://story.neodomain.cn/agent/ai-image-generation/models
如果图片 API 正常但视频 API 失败 → 联系管理员确认视频服务权限
如果全部失败 → 重新登录获取新 token（走认证流程）

2. 模型不支持某 generationType

现象：❌ Failed: 模型 xxx 不支持 YYY 类型

原因：不是所有模型都支持所有生成类型。

解决方案：

neo-video-2-0 / neo-video-2-0-fast → 仅支持 UNIVERSAL_TO_VIDEO
kling-video-o1 / kling-v3-omni → 仅支持 UNIVERSAL_TO_VIDEO
veo-3.1-* → 支持 REFERENCE_TO_VIDEO（多图参考）
其他模型 → 通常支持 TEXT_TO_VIDEO 和 IMAGE_TO_VIDEO

正确选择：

多张角色图 → 用 neo-video-2-0 + UNIVERSAL_TO_VIDEO
单张首帧 → 用 doubao-seedance-1-5-pro + IMAGE_TO_VIDEO
纯文字 → 用 doubao-seedance-1-5-pro + TEXT_TO_VIDEO

3. UNIVERSAL_TO_VIDEO 提示词写法错误

错误示例：--prompt "蓝白校服的男生和穿碎花裙子的女生在校园里散步"

正确示例：--prompt "参考@图片 1 的男生和@图片 2 的女生，两人在阳光明媚的校园里并肩散步，镜头缓慢跟随"

规则：

--image-urls 中第 1 个 URL → 用 @图片 1 引用
--image-urls 中第 2 个 URL → 用 @图片 2 引用
--video-urls 中第 1 个 URL → 用 @视频 1 引用
--audio-urls 中第 1 个 URL → 用 @音频 1 引用
必须在 prompt 中明确引用每个素材，不要用"那张图"等模糊表达

4. 认证服务不可用

现象：Authentication service unavailable, please try again

原因：Neodomain 服务端认证系统临时故障（可能在重启）

解决方案：等待 5-10 分钟后重试

意图识别与路径选择

根据用户意图选择正确路径：

用户意图	路径
生成图片（无参考图）	`generate_image.py` → TEXT_TO_IMAGE
生成图片（有参考图/角色一致性）	`generate_image_ref.py`
生成视频（纯文字描述）	`generate_video.py` → `TEXT_TO_VIDEO`
生成视频（有参考图/首帧）	`generate_video.py` → `IMAGE_TO_VIDEO`
生成视频（多张参考图保持一致性）	`generate_video.py` → `REFERENCE_TO_VIDEO`（仅 Veo 3.1）
生成视频（多模态：图 + 视频 + 音频组合）	`generate_video.py` → `UNIVERSAL_TO_VIDEO`（Universal 模型）
动作迁移（把参考视频动作转移到图片人物上）	`motion_control.py`
故事板/分镜批量生视频	`batch_video.py`

Model Selection Logic

图片模型选择

有参考图？
├─ 是 → generate_image_ref.py，模型用 doubao-seedream-5-0-260128
└─ 否 → generate_image.py
        ├─ 追求高性价比 → doubao-seedream-5-0-260128 (25pts)
        ├─ 追求最高质量 → gemini-3-pro-image-preview (100pts)
        └─ 默认/普通需求 → gemini-3.1-flash-image-preview (90pts)

视频模型选择

有多模态素材（视频/音频参考）？
└─ 是 → UNIVERSAL_TO_VIDEO
        ├─ 追求最高品质 → neo-video-2-0
        ├─ 追求速度/性价比 → neo-video-2-0-fast
        └─ 需要高分辨率 (1080p) → kling-v3-omni 或 kling-video-o1

有多张参考图（保持角色一致性）？
└─ 是 → REFERENCE_TO_VIDEO，模型用 veo-3.1-generate-preview

有参考图（图生视频）？
└─ 是 → IMAGE_TO_VIDEO
        ├─ 需要音频 → doubao-seedance-1-5-pro-251215 或 kling-v3
        ├─ 需要首尾帧精确控制 → kling-v3 或 kling-v2-6
        ├─ 需要超高清 4K → veo-3.1-generate-preview
        ├─ 需要超长时长 (15s+) → kling-v3(最长 15s) 或 vidu-q3-pro(最长 16s)
        └─ 默认 → doubao-seedance-1-5-pro-251215

纯文字生视频？
└─ 是 → TEXT_TO_VIDEO
        ├─ 需要音频 → doubao-seedance-1-5-pro-251215 或 kling-v3
        ├─ 高性价比 → doubao-seedance-1-0-pro-fast-251015
        └─ 默认 → doubao-seedance-1-5-pro-251215

视频参数选择规则

resolution：用户未指定时默认 720p；明确要求高清用 1080p；明确要求超清用 4K（仅 Veo 3.1 支持）
duration：用户未指定时默认 8s；需注意各模型上限（见下表），不要超出范围
aspect-ratio：根据用途自主判断——竖屏内容用 9:16，横屏用 16:9，方形用 1:1；IMAGE_TO_VIDEO 模式下此参数无效，无需传入
generate-audio：用户提到"有声音"/"带音频"/"有背景音乐"时自动加上

Authentication

# Step 1：发送验证码（询问用户手机号或邮箱后执行）
python3 {baseDir}/scripts/login.py --send-code --contact "手机号或邮箱"

# Step 2：用户提供验证码后登录
python3 {baseDir}/scripts/login.py --login --contact "手机号或邮箱" --code "验证码"

Step 2 可能出现两种结果：

单一身份：直接输出 accessToken，告知用户设置到 NEODOMAIN_ACCESS_TOKEN 环境变量。
多身份：输出身份列表（含编号、类型、昵称、企业名、userId），需执行 Step 3 选择身份：

# Step 3：选择身份（仅在 Step 2 返回多身份时执行）
python3 {baseDir}/scripts/login.py --select-identity --contact "手机号或邮箱" --user-id "选中的userId"

Step 3 成功后输出 accessToken，告知用户设置到 NEODOMAIN_ACCESS_TOKEN 环境变量。

Image Generation

generate_image.py（文生图 / 图生图）

python3 {baseDir}/scripts/generate_image.py \
  --prompt "A beautiful mountain landscape, golden hour, cinematic" \
  --model "doubao-seedream-5-0-260128" \
  --aspect-ratio "16:9" \
  --size "2K" \
  --token $NEODOMAIN_ACCESS_TOKEN

参数	说明	默认值
`--prompt`	图片描述	必填
`--model`	模型 ID	`gemini-3.1-flash-image-preview`
`--aspect-ratio`	`1:1`, `16:9`, `9:16`, `4:3`, `3:4`	`1:1`
`--num-images`	`1` 或 `4`	`1`
`--size`	`1K`, `2K`, `4K`	`2K`
`--negative-prompt`	负向提示词	-
`--guidance-scale`	提示词遵循度 (1.0-20.0)	`7.5`
`--seed`	随机种子	随机
`--output-format`	`jpeg`, `png`, `webp`	`jpeg`
`--output-dir`	保存目录	`./output`

可用模型：

模型 ID	费用	支持尺寸	特点
`gemini-2.5-flash-image`	30 pts	1K	快速低价
`gemini-3.1-flash-image-preview`	90 pts	1K, 2K, 4K	均衡
`gemini-3-pro-image-preview`	100 pts	2K, 4K	最高质量
`doubao-seedream-5-0-260128`	25 pts	2K, 3K	最高性价比，推荐参考图用
`doubao-seedream-4-5-251128`	30 pts	2K, 4K	-
`doubao-seedream-4-0-250828`	25 pts	2K, 4K	-
`gpt-image-1.5`	100 pts	1K	GPT 风格
`Midjourney-niji 7`	30 pts	1K	二次元/动漫
`Midjourney-v 7`	30 pts	1K	艺术风格

generate_image_ref.py（参考图生图 / 角色一致性）

python3 {baseDir}/scripts/generate_image_ref.py \
  --prompt "A woman walking in a forest" \
  --reference-image "https://example.com/character1.jpg" \
  --reference-image "https://example.com/character2.jpg" \
  --model "doubao-seedream-5-0-260128" \
  --aspect-ratio "16:9" \
  --token $NEODOMAIN_ACCESS_TOKEN

--reference-image 可多次指定，上限 10 张。其余参数同 generate_image.py，默认模型为 doubao-seedream-5-0-260128。

Video Generation

generate_video.py

统一入口，通过 --generation-type 区分模式。

TEXT_TO_VIDEO（文生视频）

python3 {baseDir}/scripts/generate_video.py \
  --prompt "A serene lake at dawn, mist rising, cinematic wide shot" \
  --model "doubao-seedance-1-5-pro-251215" \
  --generation-type "TEXT_TO_VIDEO" \
  --aspect-ratio "16:9" \
  --resolution "720p" \
  --duration "8s" \
  --generate-audio \
  --token $NEODOMAIN_ACCESS_TOKEN

IMAGE_TO_VIDEO（图生视频）

# 首帧必填，尾帧可选（需模型支持首尾帧）；宽高比自动按参考图，无需指定
python3 {baseDir}/scripts/generate_video.py \
  --prompt "The camera slowly pans across the landscape" \
  --model "kling-v3" \
  --generation-type "IMAGE_TO_VIDEO" \
  --first-frame "https://example.com/image.jpg" \
  --last-frame "https://example.com/end.jpg" \
  --resolution "1080p" \
  --duration "5s" \
  --generate-audio \
  --token $NEODOMAIN_ACCESS_TOKEN

REFERENCE_TO_VIDEO（多图参考生视频）

仅 veo-3.1-generate-preview / veo-3.1-fast-generate-preview 支持。

python3 {baseDir}/scripts/generate_video.py \
  --prompt "Characters interacting in a scene" \
  --model "veo-3.1-generate-preview" \
  --generation-type "REFERENCE_TO_VIDEO" \
  --image-urls "https://example.com/ref1.jpg,https://example.com/ref2.jpg" \
  --aspect-ratio "16:9" \
  --resolution "1080p" \
  --duration "8s" \
  --generate-audio \
  --token $NEODOMAIN_ACCESS_TOKEN

UNIVERSAL_TO_VIDEO（多模态组合生视频）

支持图片、视频、音频混合参考。必须在 prompt 中用 @图片 1/@图片 2/@视频 1/@音频 1 精确引用对应素材（顺序即编号）。

python3 {baseDir}/scripts/generate_video.py \
  --prompt "参考@图片 1 的男生和@图片 2 的女生，两人在阳光明媚的校园里并肩散步，镜头缓慢跟随" \
  --model "neo-video-2-0" \
  --generation-type "UNIVERSAL_TO_VIDEO" \
  --image-urls "https://example.com/boy.jpg,https://example.com/girl.jpg" \
  --resolution "720p" \
  --duration "5s" \
  --token $NEODOMAIN_ACCESS_TOKEN

Universal 提示词公式： @素材引用 + 主体描述 + 动作/场景 + 镜头语言 + 风格美学

@素材引用规则（重要！）：

--image-urls 中第 1 个 URL → 用 @图片 1 引用
--image-urls 中第 2 个 URL → 用 @图片 2 引用
--video-urls 中第 1 个 URL → 用 @视频 1 引用
--audio-urls 中第 1 个 URL → 用 @音频 1 引用
必须在 prompt 开头明确引用每个素材，不要用"那张图""这个角色"等模糊表达

错误示例 ❌：

--prompt "蓝白校服的男生和穿碎花裙子的女生在校园里散步"
--image-urls "boy.jpg,girl.jpg"

正确示例 ✅：

--prompt "参考@图片 1 的蓝白校服男生和@图片 2 的碎花裙子女生，两人在阳光明媚的校园里并肩散步，镜头缓慢跟随"
--image-urls "boy.jpg,girl.jpg"

适用模型：neo-video-2-0, neo-video-2-0-fast, kling-video-o1, kling-v3-omni

generate_video.py 完整参数表

参数	说明	默认值
`--prompt`	视频描述	必填
`--model`	模型 ID	`doubao-seedance-1-5-pro-251215`
`--generation-type`	`TEXT_TO_VIDEO` / `IMAGE_TO_VIDEO` / `REFERENCE_TO_VIDEO` / `UNIVERSAL_TO_VIDEO`	`TEXT_TO_VIDEO`
`--first-frame`	首帧图片 URL（I2V 必填）	-
`--last-frame`	尾帧图片 URL（可选，需模型支持）	-
`--image-urls`	参考图 URL 逗号分隔（R2V 必填；U2V 可选，→ `imageUrls`）	-
`--video-urls`	参考视频 URL 逗号分隔（U2V 可选，→ `referenceVideoUrls`）	-
`--audio-urls`	参考音频 URL 逗号分隔（U2V 可选，→ `audioUrl`）	-
`--aspect-ratio`	`16:9`/`9:16`/`1:1`/`4:3`/`3:4`/`21:9`/`9:21`（T2V/R2V 有效；I2V 无效）	`16:9`
`--resolution`	`480p`/`720p`/`768p`/`1080p`/`2k`/`4K`（各模型范围不同）	`720p`
`--duration`	时长如 `5s`/`8s`/`10s`（各模型范围不同）	`8s`
`--fps`	帧率	`24`
`--seed`	随机种子	随机
`--generate-audio`	生成音频（flag）	false
`--enhance-prompt`	增强提示词（flag）	false
`--negative-prompt`	负向提示词	-
`--output-dir`	保存目录	`./output`

各模型支持范围（Cascading）

模型 ID	类型	分辨率	时长	音频	首尾帧
`doubao-seedance-1-5-pro-251215`	T2V/I2V	480p, 720p, 1080p	4–12s	✅	✅
`doubao-seedance-1-0-pro-250528`	T2V/I2V	720p, 1080p	2–10s	❌	✅
`doubao-seedance-1-0-pro-fast-251015`	T2V/I2V	720p, 1080p	3–10s	❌	❌
`kling-v3`	T2V/I2V	720p, 1080p	3–15s	✅	✅
`kling-v2-6`	T2V/I2V	1080p	5s, 10s	✅	✅
`kling-v2-5-turbo`	T2V/I2V	720p, 1080p	5s, 10s	❌	✅
`kling-v2-1`	I2V 仅	720p, 1080p	5s, 10s	❌	✅
`vidu-q3-pro`	T2V/I2V	720p, 1080p, 2k¹	5–16s	✅	✅
`vidu-q2-pro`	I2V 仅	720p, 1080p	5s, 8s	❌	✅
`wan2.6`	T2V/I2V	720p, 1080p	5s, 10s, 15s	✅	❌
`wan2.6-i2v-flash`	I2V 仅	720p, 1080p	5s, 10s, 15s	✅	❌
`MiniMax-Hailuo-2.3`	T2V/I2V	768p, 1080p	6s, 10s	❌	❌
`MiniMax-Hailuo-2.3-Fast`	T2V/I2V	768p, 1080p	6s, 10s	❌	❌
`MiniMax-Hailuo-02`	T2V/I2V	768p, 1080p	6s, 10s	❌	✅
`veo-3.1-generate-preview`	T2V/I2V/R2V	720p, 1080p, 4K	4s, 6s, 8s	✅	✅
`veo-3.1-fast-generate-preview`	T2V/I2V/R2V	720p, 1080p, 4K	4s, 6s, 8s	✅	✅

¹ Vidu Q3 Pro 的 2k 仅在 I2V 模式下支持。 T2V 宽高比：Doubao 支持 16:9/9:16/1:1/4:3/3:4/21:9/9:21；Kling/Vidu/Wan 支持 16:9/9:16/1:1；Hailuo 仅 16:9；Veo 支持 16:9/9:16。

各模型支持范围（Universal，--generation-type UNIVERSAL_TO_VIDEO）

模型 ID	分辨率	时长	音频	首尾帧	最大参考数
`neo-video-2-0`	480p, 720p	4–15s	✅	✅	图×9, 视频×3, 音频×3
`neo-video-2-0-fast`	480p, 720p	4–12s	✅	✅	图×9, 视频×3, 音频×3
`kling-video-o1`	720p, 1080p	3–10s	❌	❌	图×12, 视频×1
`kling-v3-omni`	720p, 1080p	3–15s	✅	❌	图×12, 视频×1

motion_control.py（动作迁移）

将参考视频的人物动作迁移到参考图片上：

python3 {baseDir}/scripts/motion_control.py \
  --image "https://example.com/ref_image.jpg" \
  --video "https://example.com/ref_video.mp4" \
  --prompt "Make the character dance" \
  --mode "pro" \
  --duration 5000 \
  --token $NEODOMAIN_ACCESS_TOKEN

参数	说明	默认值
`--image`	参考图片 URL	必填
`--video`	参考动作视频 URL	必填
`--prompt`	附加文字控制	-
`--mode`	`std`（标准）/ `pro`（专业）	`std`
`--orientation`	角色朝向来源：`image` / `video`	`image`
`--keep-original-sound`	保留原视频声音：`yes` / `no`	`yes`
`--duration`	时长（毫秒）	`5000`
`--output-dir`	保存目录	`./output`

batch_video.py（批量分镜生视频）

需要 pip install oss2（用于上传本地图片到 OSS）。默认使用 doubao-seedance-1-5-pro-251215，IMAGE_TO_VIDEO，720p/5s。

python3 {baseDir}/scripts/batch_video.py \
  --storyboard-dir ./storyboards \
  --output-dir ./output/videos \
  --start 1 \
  --end 17 \
  --token $NEODOMAIN_ACCESS_TOKEN

参数	说明	默认值
`--storyboard-dir`	分镜图片目录（命名格式：`shot_01_*.jpeg`）	必填
`--output-dir`	视频输出目录	必填
`--start`	起始镜头编号	`1`
`--end`	结束镜头编号	`17`

Output

所有脚本完成后自动下载到输出目录：

图片：image_1.jpg / .png / .webp
视频：video.mp4 + thumbnail.jpg
批量视频：video_01.mp4, video_02.mp4, ...
metadata.json：任务 ID、参数、文件 URL 等详情

When it activates

Automatically, when a task matches. Use when user wants to create AI-generated images or videos using the Neodomain platform.

About this skill

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LLM judge · does the skill do what it claims

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LLM judge · policy & harmful-content review

Source

Imported

LeoYeAI / openclaw-master-skills

skills/neo-ai/SKILL.md

View on GitHub ↗

License MITImported 8/2/2026Version v1Bundled 10 files · scripts

Illustrative Want to see what leoyeai/neodomain-ai 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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Neodomain AI Content Generator

核心行为规范

⚠️ 常见问题与解决方案 (FAQ)

1. Token has been revoked (errCode 2001)

2. 模型不支持某 generationType

3. UNIVERSAL_TO_VIDEO 提示词写法错误

4. 认证服务不可用

意图识别与路径选择

Model Selection Logic

图片模型选择

视频模型选择

视频参数选择规则

Authentication

Image Generation

generate_image.py（文生图 / 图生图）

generate_image_ref.py（参考图生图 / 角色一致性）

Video Generation

generate_video.py

TEXT_TO_VIDEO（文生视频）

IMAGE_TO_VIDEO（图生视频）

REFERENCE_TO_VIDEO（多图参考生视频）

UNIVERSAL_TO_VIDEO（多模态组合生视频）

generate_video.py 完整参数表

各模型支持范围（Cascading）

各模型支持范围（Universal，--generation-type UNIVERSAL_TO_VIDEO）

motion_control.py（动作迁移）

batch_video.py（批量分镜生视频）

Output

When it activates

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