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Ezviz Open PTZ Control (萤石开放平台云台设备控制) · leoyeai | DecimalAI

Industryby leoyeai

Ezviz Open PTZ Control (萤石开放平台云台设备控制)

萤石开放平台云台设备控制技能。支持设备列表查询、设备状态查询、云台控制 (PTZ)、预置点管理等功能。

Never made a case worse

SkillScore

SkillScore84/100

Test results 84

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

40%84%of test cases passed +44 pts

Without skill10 of 25

With skill21 of 25

11 fixed10 passed either way4 still failing0 broke

Measured on gemini-3.6-flash8/8/2026v122 comparable

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskWhat numerical direction parameter is passed to `ptz_start` for automatic PTZ control 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-ezviz-open-ptz-control
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-open-ptz-control")
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-open-ptz-control

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-open-ptz-control/SKILL.md https://app.decimal.ai/s/leoyeai-ezviz-open-ptz-control/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/leoyeai-ezviz-open-ptz-control/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-open-ptz-control

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-open-ptz-control")
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-open-ptz-control/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-open-ptz-control/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-open-ptz-control

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-open-ptz-control")
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-open-ptz-control/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/leoyeai-ezviz-open-ptz-control/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-open-ptz-control

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-open-ptz-control")
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-open-ptz-control/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/leoyeai-ezviz-open-ptz-control/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-open-ptz-control

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-open-ptz-control")
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-open-ptz-control/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/leoyeai-ezviz-open-ptz-control/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-open-ptz-control

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-open-ptz-control")
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-open-ptz-control/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-open-ptz-control/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-open-ptz-control

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-open-ptz-control")
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-open-ptz-control/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/leoyeai-ezviz-open-ptz-control/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-open-ptz-control

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-open-ptz-control")
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-open-ptz-control/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-open-ptz-control

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-open-ptz-control")
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-open-ptz-control/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/leoyeai-ezviz-open-ptz-control/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-open-ptz-control

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-open-ptz-control")
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-open-ptz-control/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/leoyeai-ezviz-open-ptz-control/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-open-ptz-control

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-open-ptz-control")
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-open-ptz-control/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/leoyeai-ezviz-open-ptz-control/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-open-ptz-control

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-open-ptz-control")
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-open-ptz-control/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/leoyeai-ezviz-open-ptz-control/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-open-ptz-control

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-open-ptz-control")
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-open-ptz-control/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/leoyeai-ezviz-open-ptz-control/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-open-ptz-control

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-open-ptz-control/SKILL.md https://app.decimal.ai/s/leoyeai-ezviz-open-ptz-control/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/leoyeai-ezviz-open-ptz-control/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-open-ptz-control/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/leoyeai-ezviz-open-ptz-control.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 Open PTZ Control (萤石开放平台云台设备控制)

萤石开放平台云台设备控制，支持设备查询、云台控制、预置点管理等功能。

⚠️ 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	Token 缓存	⚠️ 注意	Token 缓存在 `/tmp/ezviz_global_token_cache/` (权限 600)
3	API 域名	✅ 已验证	`openai.ys7.com` 是萤石官方 API 端点（`openai` = Open API，不是 AI）
4	代码审查	✅ 推荐	审查 `scripts/main.py` 和 `lib/token_manager.py`

🔒 凭证获取优先级

凭证获取优先级（从高到低）：

┌─────────────────────────────────────────────────────────────┐
│ 1. 环境变量 (最高优先级 - 推荐)                                │
│    ├─ EZVIZ_APP_KEY                                         │
│    └─ EZVIZ_APP_SECRET                                      │
│    ✅ 优点：不读取配置文件，完全隔离                           │
├─────────────────────────────────────────────────────────────┤
│ 2. 命令行参数 (最低优先级)                                     │
│    python3 main.py appKey appSecret <command>               │
└─────────────────────────────────────────────────────────────┘

安全建议:

✅ 最佳实践: 使用环境变量，完全避免配置文件读取
✅ 隔离配置: 在专用配置文件只存放萤石凭证，不混用其他服务
⚠️ 风险缓解: 设置环境变量覆盖配置文件（即使配置文件存在也会被忽略）

⚠️ API 域名验证

重要: openai.ys7.com 是萤石官方 API 域名（openai = Open API，不是人工智能）

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

# 验证 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
whois ys7.com

官方文档: https://open.ys7.com/

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"

# 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，仅开通云台控制相关权限

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
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"

可选环境变量：

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

运行

python3 {baseDir}/scripts/main.py

命令行参数：

# 查询设备列表
python3 {baseDir}/scripts/main.py appKey appSecret list

# 查询设备状态
python3 {baseDir}/scripts/main.py appKey appSecret status BF6985110

# 查询设备能力集
python3 {baseDir}/scripts/main.py appKey appSecret capacity BF6985110

# 云台控制（向上）
python3 {baseDir}/scripts/main.py appKey appSecret ptz_start BF6985110 1 0 1

# 停止云台
python3 {baseDir}/scripts/main.py appKey appSecret ptz_stop BF6985110 1

# 调用预置点
python3 {baseDir}/scripts/main.py appKey appSecret preset_move BF6985110 1 1

工作流程

1. 获取 Token (appKey + appSecret → accessToken)
       ↓
2. 执行操作 (根据命令调用对应 API)
       ↓
3. 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 Open PTZ Control (萤石开放平台云台设备控制)
======================================================================
[Time] 2026-03-19 10:00:00
[INFO] Command: list

======================================================================
[Step 1] Getting access token...
======================================================================
[INFO] Using cached global token, expires: 2026-03-26 10:00:00
[SUCCESS] Using cached token, expires: 2026-03-26 10:00:00

======================================================================
[Step 2] Executing command...
======================================================================
[INFO] Calling API: https://openai.ys7.com/api/lapp/device/list
[SUCCESS] Device list retrieved

======================================================================
RESULT
======================================================================
  Status:     success
  Total devices:  3
  Devices:
    - dev1 (Status: online)
    - dev2 (Status: online)
    - dev3 (Status: offline)
======================================================================

支持的命令

命令	功能	API 文档
`list`	查询设备列表	https://openai.ys7.com/help/680
`status [dev]`	查询设备状态	https://openai.ys7.com/help/681
`capacity [dev]`	查询设备能力集	https://openai.ys7.com/help/683
`ptz_start [dev] [ch] [dir] [spd]`	开始云台控制	https://openai.ys7.com/help/690
`ptz_stop [dev] [ch]`	停止云台控制	https://openai.ys7.com/help/691
`preset_add [dev] [ch]`	添加预置点	https://openai.ys7.com/help/692
`preset_move [dev] [ch] [idx]`	调用预置点	https://openai.ys7.com/help/694
`preset_clear [dev] [ch] [idx]`	清除预置点	https://openai.ys7.com/help/693
`mirror [dev] [ch] [cmd]`	镜像翻转	https://openai.ys7.com/help/695

云台控制参数

方向参数 (direction):

值	方向	值	方向
`0`	上	`1`	下
`2`	左	`3`	右
`4`	左上	`5`	左下
`6`	右上	`7`	右下
`8`	物理放大	`9`	物理缩小
`10`	调整近焦距	`11`	调整远焦距
`16`	自动控制

速度参数 (speed):

0 - 慢速
1 - 适中（推荐）
2 - 快速

镜像命令 (command):

0 - 上下翻转
1 - 左右翻转
2 - 中心翻转

API 接口

接口	URL	文档
获取 Token	`POST /api/lapp/token/get`	https://openai.ys7.com/help/81
设备列表	`POST /api/lapp/device/list`	https://openai.ys7.com/help/680
设备状态	`POST /api/lapp/device/info`	https://openai.ys7.com/help/681
设备能力集	`POST /api/lapp/device/capacity`	https://openai.ys7.com/help/683
云台启动	`POST /api/lapp/device/ptz/start`	https://openai.ys7.com/help/690
云台停止	`POST /api/lapp/device/ptz/stop`	https://openai.ys7.com/help/691
预置点管理	`POST /api/lapp/device/preset/*`	https://openai.ys7.com/help/692

网络端点

域名	用途
`openai.ys7.com`	萤石开放平台 API（Token、云台控制）

格式代码

设备状态:

online - 设备在线
offline - 设备离线
error - 状态查询失败

错误码:

200 - 操作成功
10002 - accessToken 过期
20007 - 设备不在线
20008 - 设备响应超时
60020 - 不支持该命令 (设备不支持此功能)

Tips

设备序列号: 字母需为大写
Token 有效期: 7 天（缓存有效期内不重复获取）
云台控制: 需要先调用 ptz_start 启动，再调用 ptz_stop 停止
预置点: 添加预置点后会自动返回预置点序号
设备兼容性: 消费级设备可能不支持部分高级功能

注意事项

⚠️ 设备支持: 不是所有设备都支持云台控制，请先确认设备能力集

⚠️ 权限要求: 需要设备控制权限，子账户需要 Permission: Config

⚠️ 操作谨慎: 云台控制会影响摄像头角度，请谨慎操作

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

🔐 Token 管理与安全

Token 缓存行为

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（与 Token 实际有效期一致）
✅ 到期前 5 分钟自动刷新
✅ 缓存文件权限 600（仅当前用户可读写）

为什么缓存 Token:

⚡ 性能: 避免每次运行都调用 API 获取 Token（减少等待时间）
🌐 稳定性: 减少 API 调用次数，降低网络失败风险
💰 限流保护: 避免频繁调用触发 API 限流

禁用 Token 缓存

如果您不希望 Token 被持久化，可以通过以下方式禁用缓存：

方法 1: 环境变量

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

方法 2: 修改代码

from token_manager import get_cached_token

# 禁用缓存
token_result = get_cached_token(app_key, app_secret, use_cache=False)

缓存文件位置

系统	路径
macOS	`/var/folders/xx/xxxx/T/ezviz_global_token_cache/`
Linux	`/tmp/ezviz_global_token_cache/`
Windows	`C:\Users\{user}\AppData\Local\Temp\ezviz_global_token_cache\`

查看缓存:

# macOS/Linux
ls -la /tmp/ezviz_global_token_cache/
cat /tmp/ezviz_global_token_cache/global_token_cache.json

# 清除缓存
rm -rf /tmp/ezviz_global_token_cache/

验证命令

# 1. 验证缓存文件权限
ls -la /tmp/ezviz_global_token_cache/global_token_cache.json
# 应该显示：-rw------- (600)

# 2. 验证缓存内容
cat /tmp/ezviz_global_token_cache/global_token_cache.json | python3 -m json.tool

# 3. 验证禁用缓存
export EZVIZ_TOKEN_CACHE=0
python3 scripts/main.py ...
# 应该显示 "Getting access token from Ezviz API" 而不是 "Using cached global token"

🔒 安全建议

1. 使用最小权限凭证

创建专用的 appKey/appSecret，仅开通必要的 API 权限
不要使用主账号凭证
定期轮换凭证（建议每 90 天）

2. 环境变量安全

# 推荐：使用 .env 文件（不要提交到版本控制）
echo "EZVIZ_APP_KEY=your_key" >> .env
echo "EZVIZ_APP_SECRET=your_secret" >> .env
chmod 600 .env

# 加载环境变量
source .env

3. 禁用缓存（高安全场景）

如果您在共享计算机或高安全环境中使用：

export EZVIZ_TOKEN_CACHE=0  # 禁用缓存
python3 scripts/main.py ...

4. 定期清理缓存

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

5. 代码完整性验证

# 验证 Python 语法
python3 -m py_compile scripts/main.py lib/token_manager.py

# 验证 AST（确保无截断）
python3 -c "import ast; ast.parse(open('scripts/main.py').read()); ast.parse(open('lib/token_manager.py').read()); print('✅ Code integrity verified')"

# 检查文件行数（应 > 300 行）
wc -l scripts/main.py lib/token_manager.py

✅ 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/main.py 和 lib/token_manager.py
验证 API 域名 — 确认 openai.ys7.com 是萤石官方端点（openai = Open API，不是 AI）
验证代码完整性 — 运行 python3 -m py_compile 检查语法，确认无截断
准备测试凭证 — 创建专用萤石应用，仅开通云台控制相关权限
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

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 — 使用测试设备验证云台控制功能
监控日志 — 检查 API 调用是否正常
验证代码完整性 — 确认文件完整无截断（wc -l 检查行数）

持续维护

定期轮换凭证 — 建议每 90 天轮换一次
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

使用场景

场景	命令	说明
📋 查看设备	`list`	获取所有设备列表
🔍 检查状态	`status [dev]`	查看设备是否在线
🎮 云台控制	`ptz_start` / `ptz_stop`	调整摄像头角度
📍 保存位置	`preset_add`	保存当前位置为预置点
🎯 调用位置	`preset_move [idx]`	移动到预置点
🔄 镜像翻转	`mirror [cmd]`	翻转摄像头画面

⚠️ 域名说明

为什么是 openai.ys7.com 而不是 open.ys7.com？

域名	用途	说明
`openai.ys7.com`	✅ API 接口	萤石开放平台 API 专用域名（`openai` = Open API，不是人工智能）
`open.ys7.com`	🌐 官方网站	萤石开放平台官网/文档入口

官方文档: https://open.ys7.com/

安全提示:

✅ openai.ys7.com 是萤石官方 API 域名
✅ 两个域名都属于萤石（ys7.com）
⚠️ 如果担心域名安全，先用测试凭证验证

更新日志

日期	版本	变更	说明
2026-03-19	1.0.5	添加代码完整性验证	回应审核关切，添加语法验证和代码完整性检查
2026-03-19	1.0.5	添加 API 域名验证说明	明确 `openai.ys7.com` 是萤石官方 API（Open API）
2026-03-19	1.0.5	完善安全审计清单	添加代码审查和完整性验证步骤
2026-03-19	1.0.4	参考设备抓图技能格式	统一 metadata 格式、安全警告、凭证优先级说明
2026-03-19	1.0.3	整合元数据到 SKILL.md	移除单独文件，所有信息整合到 SKILL.md
2026-03-19	1.0.2	添加 Token 缓存支持	使用全局 Token 管理器，与设备抓图技能一致

最后更新: 2026-03-19
版本: 1.0.5 (代码完整性验证版)

作者: EzvizOpenTeam
主页: https://openai.ys7.com/
许可证: MIT-0

When it activates

Automatically, when a task matches. Use when: 需要控制萤石云台设备、调整摄像头角度、设置预置点。 ⚠️ 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

Coding 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/ezviz-open-ptz-control/SKILL.md

View on GitHub ↗

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

Illustrative Want to see what leoyeai/ezviz-open-ptz-control 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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SkillScore

Safety

What it changes

Track record

Use this skill

Ezviz Open PTZ Control (萤石开放平台云台设备控制)

⚠️ 安全警告 (安装前必读)

🔒 凭证获取优先级

⚠️ API 域名验证

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

支持的命令

云台控制参数

API 接口

网络端点

格式代码

Tips

注意事项

🔐 Token 管理与安全

Token 缓存行为

禁用 Token 缓存

缓存文件位置

验证命令

🔒 安全建议

1. 使用最小权限凭证

2. 环境变量安全

3. 禁用缓存（高安全场景）

4. 定期清理缓存

5. 代码完整性验证

✅ 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

使用场景

⚠️ 域名说明

更新日志

When it activates

SkillSafety

Source

Other skills for the same job

Related skills

More in the registry