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Ezviz Audio Broadcast (萤石语音广播) · leoyeai | DecimalAI

Registry skillby leoyeai

Ezviz Audio Broadcast (萤石语音广播)

萤石语音广播技能。支持本地音频文件上传或文本转语音，实现语音内容下发到设备播放。

Never made a case worse

SkillScore

SkillScore74/100

Test results 74

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

17%74%of test cases passed +57 pts

Without skill4 of 23

With skill17 of 23

13 fixed4 passed either way6 still failing0 broke

Measured on gemini-3.6-flash8/8/2026v120 comparable

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskHow long is an Ezviz access token valid for, and how many minutes prior to expiration will the token manager automatically refresh it?

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-ezviz-audio-broadcast
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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast

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-ezviz-audio-broadcast/SKILL.md https://app.decimal.ai/s/leoyeai-ezviz-audio-broadcast/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/leoyeai-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast/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-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/leoyeai-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/leoyeai-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/leoyeai-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast/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-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/leoyeai-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/leoyeai-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/leoyeai-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/leoyeai-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/leoyeai-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast")
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-ezviz-audio-broadcast/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/leoyeai-ezviz-audio-broadcast/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 leoyeai-ezviz-audio-broadcast

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-ezviz-audio-broadcast/SKILL.md https://app.decimal.ai/s/leoyeai-ezviz-audio-broadcast/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/leoyeai-ezviz-audio-broadcast/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/leoyeai-ezviz-audio-broadcast/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/leoyeai-ezviz-audio-broadcast.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: v1, tested 8/8/2026
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

Ezviz Audio Broadcast (萤石语音广播)

通过萤石语音上传和下发接口，实现语音内容到设备的广播播放。

⚠️ 安全警告 (安装前必读)

在使用此技能前，请完成以下安全检查：

#	检查项	状态	说明
1	凭证权限	⚠️ 必需	使用最小权限的 AppKey/AppSecret，不要用主账号凭证
2	配置文件	⚠️ 注意	技能会读取 `~/.openclaw/config.json` 等文件中的萤石凭证
3	Token 缓存	⚠️ 注意	Token 缓存在 `/tmp/ezviz_global_token_cache/` (权限 600)
4	系统命令	⚠️ 注意	使用 `say`/`espeak`/`ffmpeg` 进行 TTS (通过 subprocess)
5	API 域名	✅ 已验证	`openai.ys7.com` 是萤石官方 API 端点
6	代码审查	✅ 推荐	审查 `scripts/audio_broadcast.py` 和 `lib/token_manager.py`

快速安全配置

# 1. 使用环境变量（优先级最高，避免配置文件意外使用）
export EZVIZ_APP_KEY="your_dedicated_app_key"
export EZVIZ_APP_SECRET="your_dedicated_app_secret"
export EZVIZ_DEVICE_SERIAL="device1,device2"

# 2. 高安全环境：禁用 Token 缓存
export EZVIZ_TOKEN_CACHE=0

# 3. 测试凭证（推荐先用测试账号）
# 登录 https://openai.ys7.com/ 创建专用应用，仅开通语音相关权限

凭证优先级

技能按以下顺序获取凭证（优先级从高到低）：

环境变量 (EZVIZ_APP_KEY, EZVIZ_APP_SECRET) ← 推荐
Channels 配置 (~/.openclaw/config.json 等)
命令行参数 (直接传入)

快速开始

安装依赖

pip install requests

设置环境变量

export EZVIZ_APP_KEY="your_app_key"
export EZVIZ_APP_SECRET="your_app_secret"
export EZVIZ_DEVICE_SERIAL="dev1,dev2,dev3"

可选环境变量：

export EZVIZ_CHANNEL_NO="1"        # 通道号，默认 1
export EZVIZ_AUDIO_FILE="/path/to/audio.mp3"  # 本地音频文件路径（二选一）
export EZVIZ_TEXT_CONTENT="语音内容文本"      # 文本内容（二选一）
export EZVIZ_VOICE_NAME="custom_name"         # 自定义语音名称
export EZVIZ_TOKEN_CACHE="1"                  # Token 缓存：1=启用 (默认), 0=禁用

Token 缓存说明:

✅ 默认启用: 技能默认使用 Token 缓存，提升效率
⚠️ 禁用缓存: 设置 EZVIZ_TOKEN_CACHE=0 每次重新获取 Token
📁 缓存位置: /tmp/ezviz_global_token_cache/global_token_cache.json
🔒 文件权限: 600 (仅所有者可读写)
⏰ 有效期: 7 天，到期前 5 分钟自动刷新

注意:

不需要设置 EZVIZ_ACCESS_TOKEN！技能会自动获取 Token
必须提供 EZVIZ_AUDIO_FILE 或 EZVIZ_TEXT_CONTENT 其中一个
设备需要支持对讲功能（support_talk=1或3）

运行

python3 {baseDir}/scripts/audio_broadcast.py

命令行参数：

# 使用本地音频文件
python3 {baseDir}/scripts/audio_broadcast.py appKey appSecret dev1 /path/to/audio.mp3 [channel_no]

# 使用文本内容（自动生成语音）
python3 {baseDir}/scripts/audio_broadcast.py appKey appSecret dev1 "语音内容文本" [channel_no]

工作流程

1. 获取 Token (appKey + appSecret → accessToken)
 ↓
2a. 如果提供音频文件：直接上传文件
2b. 如果提供文本：调用TTS生成音频文件，然后上传
 ↓
3. 下发语音 (accessToken + deviceSerial + fileUrl → 设备播放)
 ↓
4. 输出结果 (JSON + 控制台)

Token 自动获取说明

你不需要手动获取或配置 EZVIZ_ACCESS_TOKEN！

技能会自动处理 Token 的获取：

首次运行:
 appKey + appSecret → 调用萤石 API → 获取 accessToken (有效期 7 天)
 ↓
保存到缓存文件（系统临时目录）
 ↓
后续运行:
 检查缓存 Token 是否过期
 ├─ 未过期 → 直接使用缓存 Token ✅
 └─ 已过期 → 重新获取新 Token

Token 管理特性:

✅ 自动获取: 首次运行自动调用萤石 API 获取
✅ 有效期 7 天: 获取的 Token 7 天内有效
✅ 智能缓存: Token 有效期内不重复获取，提升效率
✅ 安全缓冲: 到期前 5 分钟自动刷新，避免边界问题
✅ 无需配置: 不需要手动设置 EZVIZ_ACCESS_TOKEN 环境变量
✅ 安全存储: 缓存文件存储在系统临时目录，权限 600
⚠️ 可选禁用: 设置 EZVIZ_TOKEN_CACHE=0 可禁用缓存（每次运行重新获取）

输出示例

======================================================================
Ezviz Audio Broadcast Skill (萤石语音广播)
======================================================================
[Time] 2026-03-16 16:30:00
[INFO] Target devices: 2
 - dev1 (Channel: 1)
 - dev2 (Channel: 1)
[INFO] Mode: Text-to-Speech
[INFO] Content: 接下来插播一个广告

======================================================================
[Step 1] Getting access token...
[SUCCESS] Token obtained, expires: 2026-03-23 16:30:00

======================================================================
[Step 2] Generating and uploading audio...
[INFO] Generated TTS file: /tmp/ezviz_tts_12345.mp3
[SUCCESS] Audio uploaded successfully!
[INFO] Voice Name: ad_broadcast
[INFO] File URL: https://oss-cn-shenzhen.aliyuncs.com/voice/...

======================================================================
[Step 3] Broadcasting audio to devices...
======================================================================

[Device] dev1 (Channel: 1)
[SUCCESS] Audio broadcast completed!

[Device] dev2 (Channel: 1)  
[SUCCESS] Audio broadcast completed!

======================================================================
BROADCAST SUMMARY
======================================================================
 Total devices: 2
 Success: 2
 Failed: 0
======================================================================

多设备格式

格式	示例	说明
单设备	`dev1`	默认通道 1
多设备	`dev1,dev2,dev3`	全部使用默认通道
指定通道	`dev1:1,dev2:2`	每个设备独立通道
混合	`dev1,dev2:2,dev3`	部分指定通道

API 接口

接口	URL	文档
获取 Token	`POST /api/lapp/token/get`	https://openai.ys7.com/help/81
语音上传	`POST /api/lapp/voice/upload`	https://openai.ys7.com/help/1241
语音下发	`POST /api/lapp/voice/send`	https://openai.ys7.com/help/1253

网络端点

域名	用途
`openai.ys7.com`	萤石开放平台 API（Token、语音上传、下发）

音频要求

格式	支持	限制
WAV	✅	最大5MB，最长60秒
MP3	✅	最大5MB，最长60秒
AAC	✅	最大5MB，最长60秒

注意事项

⚠️ 设备兼容性: 设备必须支持对讲功能（support_talk=1或3），否则返回错误码 20015

⚠️ 频率限制: 语音下发接口有调用频率限制，建议设备间间隔1秒以上

⚠️ 文件大小: 音频文件不能超过5MB，时长不能超过60秒

⚠️ Token 安全: Token 缓存到系统临时目录（权限 600），不写入日志，不发送到非萤石端点

⚠️ TTS依赖: 文本转语音功能依赖系统TTS服务，确保系统支持

数据流出说明

本技能会向第三方服务发送数据：

数据类型	发送到	用途	是否必需
音频文件	`openai.ys7.com` (萤石)	语音上传和下发	✅ 必需
appKey/appSecret	`openai.ys7.com` (萤石)	获取访问 Token	✅ 必需
设备序列号	`openai.ys7.com` (萤石)	请求下发	✅ 必需
EZVIZ_ACCESS_TOKEN	自动生成	每次运行自动获取	✅ 自动

数据流出说明:

✅ 萤石开放平台 (openai.ys7.com): 所有API调用 - 萤石官方 API
❌ 无其他第三方: 不会发送数据到其他服务

凭证权限建议:

使用最小权限的 appKey/appSecret
仅开通必要的 API 权限（语音上传、下发）
定期轮换凭证
不要使用主账号凭证

本地处理:

✅ Token 缓存到系统临时目录（权限 600）
✅ TTS临时文件自动清理
✅ 不记录完整 API 响应

应用场景

✅ 可选禁用缓存：设置 EZVIZ_TOKEN_CACHE=0 | 场景 | 说明 | |------|------| | 📢 安全广播 | 向监控区域发送安全提醒、紧急通知 | | 🏢 办公通知 | 办公室广播会议提醒、访客通知 | | 🏪 商业应用 | 商店促销广播、排队叫号 | | 🏠 智能家居 | 家庭语音提醒、门铃通知 | | 🏭 工厂管理 | 生产线通知、安全警示 |

使用示例

场景1: 紧急安全通知

python3 audio_broadcast.py your_key your_secret "kitchen_cam,dining_area" "注意！检测到安全隐患，请立即检查！"

场景2: 商业促销广播

export EZVIZ_TEXT_CONTENT="欢迎光临！今日特价商品限时优惠，详情请咨询店员！"
export EZVIZ_DEVICE_SERIAL="store_front,store_back"
python3 audio_broadcast.py

场景3: 使用预录制音频

python3 audio_broadcast.py your_key your_secret entrance_cam /path/to/welcome_message.mp3

API 端点

接口	URL	文档
获取 Token	`POST /api/lapp/token/get`	https://openai.ys7.com/help/81
语音上传	`POST /api/lapp/voice/upload`	https://openai.ys7.com/help/1241
语音下发	`POST /api/lapp/voice/send`	https://openai.ys7.com/help/1253

API 域名: https://openai.ys7.com (萤石开放平台)

✅ 域名验证

# 验证域名连通性
curl -I https://openai.ys7.com/api/lapp/token/get

# 检查 SSL 证书
curl -vI https://openai.ys7.com/api/lapp/token/get 2>&1 | grep -A5 "SSL certificate"

# 验证域名所有权（萤石开放平台）
whois ys7.com

官方文档: https://open.ys7.com/

⚠️ 配置文件扫描说明

技能会读取以下路径中的萤石配置（仅当环境变量未设置时）：

~/.openclaw/config.json
~/.openclaw/gateway/config.json
~/.openclaw/channels.json

配置格式:

{
  "channels": {
    "ezviz": {
      "appId": "your_app_id",
      "appSecret": "your_app_secret",
      "domain": "https://openai.ys7.com",
      "enabled": true
    }
  }
}

安全建议:

✅ 使用专用萤石凭证，不要与其他服务共享
✅ 如果不想使用配置文件扫描，设置环境变量覆盖
✅ 定期审查配置文件中的凭证权限
❌ 不要在配置文件中存储主账号凭证

禁用配置文件扫描（环境变量优先）:

export EZVIZ_APP_KEY="your_key"
export EZVIZ_APP_SECRET="your_secret"
# 环境变量优先级高于配置文件

系统依赖

Python 包:

pip install requests

系统工具 (仅 TTS 需要):

macOS: say, afconvert
Linux: espeak, ffmpeg

⚠️ 系统命令安全说明

技能通过 subprocess 调用系统 TTS 命令：

# macOS TTS
subprocess.run(['say', '-o', temp_aiff, text_with_pauses], check=True, capture_output=True)
subprocess.run(['afconvert', '-f', 'WAVE', '-d', 'LEI16@44100', temp_aiff, output_path], ...)

# Linux TTS
subprocess.run(['espeak', '-w', output_path, text], check=True, capture_output=True)
subprocess.run(['ffmpeg', '-i', input, '-acodec', 'libmp3lame', output], ...)

安全措施 (v1.0.2+):

✅ 使用列表参数调用 subprocess（避免 shell 注入）
✅ 输入验证: 文本内容经过 validate_text_input() 验证
✅ 危险字符拦截: 拒绝包含 ;, |, &, $(), 等字符的输入
✅ 长度限制: 文本内容最多 500 字符
✅ 临时文件存储在系统临时目录，使用后清理

输入验证规则:

检查项	限制	说明
空内容	❌ 拒绝	文本不能为空
长度	≤500 字符	防止过长输入
危险字符	❌ 拒绝	`;`, `
设备序列号	字母数字	只允许 `A-Za-z0-9_:,`

安全建议:

✅ 确保系统二进制文件来自可信源
✅ 在高安全环境运行前审查 text_to_speech() 函数
✅ 使用容器/沙箱隔离执行环境
✅ 输入验证提供额外保护层（防御纵深）

不使用 TTS (仅提供音频文件，避免系统命令):

python3 scripts/audio_broadcast.py appKey appSecret deviceSerial --audio-file /path/to/audio.mp3

安全说明

⚠️ 环境变量声明

必需环境变量 (在 SKILL.md metadata 中声明):

metadata:
  openclaw:
    requires:
      env: ["EZVIZ_APP_KEY", "EZVIZ_APP_SECRET", "EZVIZ_DEVICE_SERIAL"]

⚠️ 注意: 如果 Registry metadata 未显示必需环境变量，以 SKILL.md 为准。

⚠️ Token 持久化说明

默认行为:

Token 会缓存到系统临时目录（/tmp/ezviz_global_token_cache/global_token_cache.json）
缓存有效期 7 天，文件权限 600（仅所有者可读写）
所有萤石技能共享同一个全局缓存

缓存位置查询:

# macOS
ls -la /var/folders/*/T/ezviz_global_token_cache/

# Linux
ls -la /tmp/ezviz_global_token_cache/

# 查看缓存内容（脱敏）
cat /tmp/ezviz_global_token_cache/global_token_cache.json

⚠️ 潜在风险:

风险	等级	说明
Token 明文存储	🟡 中	文件权限 600，但仍是明文
跨技能共享	🟡 中	同一用户的技能可共享 Token
多用户系统	🟠 高	其他用户可能访问临时目录
临时目录清理	🟢 低	系统重启可能清理临时文件

禁用缓存 (高安全环境/共享系统):

export EZVIZ_TOKEN_CACHE=0
python3 scripts/audio_broadcast.py ...

清除缓存:

# 清除所有缓存 Token
rm -rf /tmp/ezviz_global_token_cache/

# 或使用 Token 管理器
python3 lib/token_manager.py clear

安全建议:

环境	建议
单用户个人设备	✅ 默认缓存安全（文件权限 600）
多用户共享系统	⚠️ 设置 `EZVIZ_TOKEN_CACHE=0`
高安全环境	⚠️ 禁用缓存 + 专用 OS 用户 + 容器隔离
生产环境	⚠️ 容器/VM 隔离 + 禁用缓存 + 密钥管理器

⚠️ 凭证轮换通知

⚠️ 早期版本用户必须轮换凭证！

如果您曾经使用过旧版本的 .env 文件:

🚨 您的凭证可能已泄露！

立即执行:
1. 登录 https://openai.ys7.com/
2. 删除旧应用，创建新应用
3. 获取新的 AppKey 和 AppSecret

正确做法:

❌ 不要使用 .env 文件（已删除）
✅ 使用环境变量
✅ 使用最小权限凭证
✅ 定期轮换凭证（建议每 90 天）
✅ 使用密钥管理器（生产环境）

数据流出说明

数据类型	发送到	用途
AppKey/AppSecret	`openai.ys7.com`	获取 Token
设备序列号	`openai.ys7.com`	API 调用
音频文件	`openai.ys7.com`	语音上传

代码审查

推荐审查的文件:

scripts/audio_broadcast.py - 主脚本
lib/token_manager.py - Token 管理器

代码特点:

✅ 代码未混淆，易于审查
✅ 使用 requests 库（标准做法）
✅ 使用 subprocess 带列表参数（减少 shell 注入风险）
⚠️ TTS 调用系统二进制文件（say/espeak/ffmpeg）

降低风险操作清单

安装前:

审查所有代码（scripts/, lib/）
验证 API 域名和 SSL 证书
准备测试凭证（非生产环境）
确认环境变量名称一致（EZVIZ_TEXT_CONTENT）

安装时:

设置 EZVIZ_TOKEN_CACHE=0（共享系统/多用户环境）
使用专用 OS 用户账户
在隔离环境运行（容器/VM）
使用环境变量而非 .env 文件

安装后:

验证缓存文件权限（600）
监控 API 调用日志
定期轮换凭证（90 天）
使用后清除缓存（高安全环境）
验证环境变量名称一致性

🔒 安全审计清单 (安装前完成)

根据安全审计建议，请在安装前完成以下检查：

安装前检查

审查代码 — 阅读 scripts/audio_broadcast.py 和 lib/token_manager.py
验证 API 域名 — 确认 openai.ys7.com 是萤石官方端点
准备测试凭证 — 创建专用萤石应用，仅开通语音相关权限
检查配置文件 — 审查 ~/.openclaw/*.json 中是否有敏感凭证
确认缓存位置 — 确认 /tmp/ezviz_global_token_cache/ 可接受

安装时配置

使用环境变量 — 优先使用 EZVIZ_APP_KEY 等环境变量
禁用缓存 (可选) — 高安全环境设置 EZVIZ_TOKEN_CACHE=0
最小权限凭证 — 不要使用主账号凭证
隔离环境 (可选) — 在容器/VM 中运行

安装后验证

验证缓存权限 — 确认缓存文件权限为 600
测试功能 — 使用测试设备验证广播功能
监控日志 — 检查 API 调用是否正常
记录凭证 — 安全存储凭证信息（密钥管理器）

持续维护

定期轮换凭证 — 建议每 90 天轮换一次
审查依赖 — 定期检查 requests 等依赖的安全更新
清理缓存 — 高安全环境使用后清除缓存
监控异常 — 关注异常 API 调用或错误

更新日志:

日期	版本	变更	说明
2026-03-18	1.0.3	修复 metadata	添加 `config.tokenCache` 配置说明
2026-03-18	1.0.3	明确缓存行为	默认启用缓存，支持 `EZVIZ_TOKEN_CACHE=0` 禁用
2026-03-18	1.0.2	添加输入验证	`validate_text_input()` 和 `validate_device_serial()`
2026-03-18	1.0.2	添加凭证来源警告	从配置文件读取时显示警告
2026-03-18	1.0.2	更新 metadata 格式	使用 YAML 格式，添加 warnings 字段
2026-03-18	1.0.1	修复 Token 缓存 bug	`use_cache=None` 改为 `use_cache=True`
2026-03-18	1.0.1	添加安全审计清单	根据安全建议添加完整检查清单
2026-03-18	1.0.1	明确配置文件行为	说明 `~/.openclaw/*.json` 读取逻辑
2026-03-18	1.0.1	添加 API 域名验证	提供域名和 SSL 验证命令
2026-03-18	1.0.1	添加 TTS 安全说明	说明 subprocess 调用系统命令的安全措施

最后更新: 2026-03-18
版本: 1.0.3 (缓存配置修复版)

Channels 配置（推荐）

技能支持从 OpenClaw 的 channels 配置中自动读取萤石凭证，无需单独设置环境变量。

配置方式

在 ~/.openclaw/config.json 或 ~/.openclaw/channels.json 中添加：

{
  "channels": {
    "ezviz": {
      "appId": "your_app_id",
      "appSecret": "your_app_secret",
      "domain": "https://openai.ys7.com",
      "enabled": true
    }
  }
}

配置搜索顺序

技能会按以下顺序查找配置文件：

~/.openclaw/config.json
~/.openclaw/gateway/config.json
~/.openclaw/channels.json

优先级

凭证获取优先级：

环境变量 (最高优先级)
- EZVIZ_APP_KEY
- EZVIZ_APP_SECRET
Channels 配置 (中等优先级)
- channels.ezviz.appId
- channels.ezviz.appSecret
命令行参数 (最低优先级)

优势

✅ 集中管理凭证
✅ 无需每次设置环境变量
✅ 多个技能共享同一配置
✅ 更符合 OpenClaw 最佳实践

When it activates

Automatically, when a task matches. Use when: 需要向萤石设备发送语音通知、广播、提醒等音频内容。 ⚠️ 安全要求：必须设置 EZVIZ_APP_KEY 和 EZVIZ_APP_SECRET 环境变量，使用最小权限凭证。

About this skill

Automatic

DevOps & SRE pack

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/2/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

LeoYeAI / openclaw-master-skills

skills/hsa-test2/SKILL.md

View on GitHub ↗

License MITImported 8/2/2026Version v1Bundled 1 file · scripts

Illustrative Want to see what leoyeai/ezviz-audio-broadcast 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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ezviz-audio-broadcast通过萤石语音上传和下发接口，实现语音内容到设备的广播播放。Near-identical description+64 pts pass-rate lift

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SkillScore

Safety

What it changes

Track record

Use this skill

Ezviz Audio Broadcast (萤石语音广播)

⚠️ 安全警告 (安装前必读)

快速安全配置

凭证优先级

快速开始

安装依赖

设置环境变量

运行

工作流程

Token 自动获取说明

输出示例

多设备格式

API 接口

网络端点

音频要求

注意事项

数据流出说明

应用场景

使用示例

API 端点

✅ 域名验证

⚠️ 配置文件扫描说明

系统依赖

⚠️ 系统命令安全说明

安全说明

⚠️ 环境变量声明

⚠️ Token 持久化说明

⚠️ 凭证轮换通知

数据流出说明

代码审查

降低风险操作清单

🔒 安全审计清单 (安装前完成)

安装前检查

安装时配置

安装后验证

持续维护

Channels 配置（推荐）

配置方式

配置搜索顺序

优先级

优势

When it activates

SkillSafety

Source

Other skills for the same job

Related skills

More in the registry