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Btpanel · leoyeai | DecimalAI

DevOpsby leoyeai

Btpanel

宝塔面板(BT-Panel)运维监控技能，提供服务器资源监控、网站状态检查、服务状态检查、SSH安全审计、计划任务管理、日志读取等功能

SkillScore

SkillScore59/100

Test results 59

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

23%59%of test cases passed +36 pts

Without skill5 of 22

With skill13 of 22

8 fixed5 passed either way9 still failing0 broke

Measured on gemini-3.6-flash8/6/2026v121 comparable

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskNginx on server web-01 is throwing HTTP 500 responses. Fetch the last 200 lines of the Nginx error log for this server using the CLI script.

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-btpanel
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-btpanel")
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-btpanel

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

Copy SKILL.md

Save it in your project, as

.claude/skills/leoyeai-btpanel/SKILL.md

This gets SKILL.md only. The skill's 7 other files are not included.

Other ways to add it

Claude Code docs

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

Install

pip install "decimalai[claude-agent-sdk]"
decimalai skills add leoyeai-btpanel

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-btpanel")
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-btpanel/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-btpanel/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 7 other files are not included.

Other ways to add it

Claude Agent SDK docs

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

Install

pip install "decimalai[openai-agents]"
decimalai skills add leoyeai-btpanel

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-btpanel")
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-btpanel/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/leoyeai-btpanel/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 7 other files are not included.

Other ways to add it

OpenAI Agents docs

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

Install

pip install "decimalai[openai]"
decimalai skills add leoyeai-btpanel

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-btpanel")
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-btpanel/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/leoyeai-btpanel/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 7 other files are not included.

Other ways to add it

OpenAI SDK docs

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

Install

pip install "decimalai[anthropic]"
decimalai skills add leoyeai-btpanel

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-btpanel")
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-btpanel/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/leoyeai-btpanel/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 7 other files are not included.

Other ways to add it

Anthropic docs

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

Install

pip install "decimalai[google-genai]"
decimalai skills add leoyeai-btpanel

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-btpanel")
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-btpanel/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-btpanel/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 7 other files are not included.

Other ways to add it

Gemini API docs

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

Install

pip install "decimalai[langchain]" langchain-openai
decimalai skills add leoyeai-btpanel

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-btpanel")
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-btpanel/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/leoyeai-btpanel/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 7 other files are not included.

Other ways to add it

LangChain docs

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

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"
decimalai skills add leoyeai-btpanel

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-btpanel")
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-btpanel/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 7 other files are not included.

Other ways to add it

CrewAI docs

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

Install

pip install "decimalai[adk]"
decimalai skills add leoyeai-btpanel

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-btpanel")
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-btpanel/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/leoyeai-btpanel/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 7 other files are not included.

Other ways to add it

Google ADK docs

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

Install

pip install "decimalai[pydantic-ai]"
decimalai skills add leoyeai-btpanel

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-btpanel")
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-btpanel/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/leoyeai-btpanel/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 7 other files are not included.

Other ways to add it

Pydantic AI docs

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

Install

pip install "decimalai>=0.16" deepagents
decimalai skills add leoyeai-btpanel

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-btpanel")
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-btpanel/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/leoyeai-btpanel/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 7 other files are not included.

Other ways to add it

Deep Agents docs

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

Install

pip install "decimalai>=0.16" agent-framework
decimalai skills add leoyeai-btpanel

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-btpanel")
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-btpanel/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/leoyeai-btpanel/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 7 other files are not included.

Other ways to add it

Microsoft Agent Framework docs

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

Install

pip install "decimalai>=0.16" strands-agents
decimalai skills add leoyeai-btpanel

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-btpanel")
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-btpanel/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/leoyeai-btpanel/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 7 other files are not included.

Other ways to add it

Strands docs

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

pip install "decimalai>=0.15"
decimalai skills add leoyeai-btpanel

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

Copy SKILL.md

Save it in your project, as

.agents/skills/leoyeai-btpanel/SKILL.md

This gets SKILL.md only. The skill's 7 other files are not included.

Other ways to add it

Cursor and other editors docs

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

Get the file

curl -fsSL https://app.decimal.ai/s/leoyeai-btpanel/SKILL.md

Read the summary as JSON

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

This gets SKILL.md only. The skill's 7 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 8/6/2026
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

宝塔面板运维监控

宝塔面板服务器的全方位运维监控工具，支持多服务器管理、资源监控、网站状态检查、服务状态检查、SSH安全审计、计划任务管理等功能。

宝塔面板

图标资源

技能包提供以下图标文件，可在生成报告时引用：

文件	格式	用途
`icon/bt-logo.svg`	SVG	矢量图标，适合缩放

使用示例（生成报告时）：

# 服务器巡检报告

![宝塔面板](icon/bt-logo.svg)

## 概述
...

AI 使用约束

本技能用于查询和展示服务器状态数据，AI应遵循以下原则：

数据中立：如实展示监控数据，不夸大或缩小问题严重性
客观分析：基于阈值配置给出告警，避免主观判断
数据驱动：建议和结论应基于实际数据，不得臆测
隐私保护：不主动泄露服务器敏感信息（如IP、Token、域名）
执行前告知：由于接口数据较多，获取和分析需要一定时间，AI应先向用户简述即将执行的操作步骤，然后再执行命令获取数据

执行流程示例：

AI: 我将为您执行以下操作：
    1. 获取服务器系统资源状态（CPU、内存、磁盘）
    2. 检查网站运行状态
    3. 检查服务运行状态
    正在获取数据，请稍候...
    [执行命令]
    [展示结果和分析]

服务器配置管理

重要: 没有服务器信息时需要添加

使用配置工具管理服务器：

# 查看帮助
python3 {baseDir}/scripts/bt-config.py -h

# 添加服务器
python3 {baseDir}/scripts/bt-config.py add -n prod-01 -H https://panel.example.com:8888 -t YOUR_TOKEN

# 列出服务器
python3 {baseDir}/scripts/bt-config.py list

# 设置阈值
python3 {baseDir}/scripts/bt-config.py threshold --cpu 75 --memory 80

常用场景

场景一：初次使用配置服务器

当用户第一次使用本技能时，需要先配置服务器连接信息：

# 添加服务器（需要面板地址和API Token）
python3 {baseDir}/scripts/bt-config.py add -n prod-01 -H https://panel.example.com:8888 -t YOUR_API_TOKEN

# 查看已配置的服务器
python3 {baseDir}/scripts/bt-config.py list

获取API Token的方法：

登录宝塔面板
进入「面板设置」->「API接口」
点击「获取API Token」

用户意图识别：

"帮我配置宝塔服务器" → 引导用户添加服务器配置
"添加一台服务器" → 执行 bt-config.py add
"查看有哪些服务器" → 执行 bt-config.py list

场景二：多服务器资源汇总

当用户需要了解所有服务器的整体运行状态时：

# 查看所有服务器的资源使用情况
python3 {baseDir}/scripts/monitor.py --format table

# 查看所有服务器的网站状态汇总
python3 {baseDir}/scripts/sites.py

# 查看所有服务器的服务状态
python3 {baseDir}/scripts/services.py

用户意图识别：

"服务器整体情况怎么样" → 执行 monitor.py
"所有服务器健康状态" → 执行 monitor.py + sites.py
"多服务器资源使用情况" → 执行 monitor.py --format table

场景三：单台服务器日常巡检

当用户需要对单台服务器进行全面检查时：

# 指定服务器名称进行各项检查
python3 {baseDir}/scripts/monitor.py --server prod-01 --format table
python3 {baseDir}/scripts/sites.py --server prod-01
python3 {baseDir}/scripts/services.py --server prod-01
python3 {baseDir}/scripts/ssh.py --status --server prod-01
python3 {baseDir}/scripts/crontab.py --backup-only --server prod-01

用户意图识别：

"检查 prod-01 这台服务器" → 执行上述检查命令
"帮我日常巡检" → 执行系统监控、网站状态、服务状态检查
"这台服务器有问题吗" → 执行全面检查并汇总告警

场景四：网站SSL证书检查

当用户关心SSL证书是否即将过期时：

# 查看SSL即将过期的网站
python3 {baseDir}/scripts/sites.py --filter ssl-warning

# 查看SSL已过期的网站
python3 {baseDir}/scripts/sites.py --filter ssl-expired

用户意图识别：

"SSL证书快过期了吗" → 执行 sites.py --filter ssl-warning
"有哪些网站证书过期了" → 执行 sites.py --filter ssl-expired

场景五：安全审计

当用户需要进行安全检查时：

# 查看SSH登录失败记录
python3 {baseDir}/scripts/ssh.py --logs --filter failed

# 搜索特定IP的登录记录
python3 {baseDir}/scripts/ssh.py --logs --search 192.168.1.100

# 查看SSH服务状态
python3 {baseDir}/scripts/ssh.py --status

用户意图识别：

"有没有异常登录" → 执行 ssh.py --logs --filter failed
"查一下这个IP的登录记录" → 执行 ssh.py --logs --search IP
"SSH安全检查" → 执行 ssh.py --status 和 ssh.py --logs

场景六：服务故障排查

当某个服务出现问题时：

# 查看服务状态
python3 {baseDir}/scripts/services.py --server prod-01

# 查看服务错误日志
python3 {baseDir}/scripts/logs.py --server prod-01 --service nginx --lines 200
python3 {baseDir}/scripts/logs.py --server prod-01 --service redis

用户意图识别：

"Nginx/Apache/Redis出问题了" → 查看服务状态 + 查看错误日志
"服务报错了，帮我看看日志" → 执行 logs.py 查看对应服务日志

场景七：备份任务检查

当用户关心备份是否正常时：

# 查看所有备份任务
python3 {baseDir}/scripts/crontab.py --backup-only

# 查看特定备份任务的执行日志
python3 {baseDir}/scripts/crontab.py --logs --task-id 11

用户意图识别：

"备份任务正常吗" → 执行 crontab.py --backup-only
"查看备份日志" → 执行 crontab.py --logs --task-id ID

版本要求

宝塔面板: >= 9.0.0
Python: >= 3.10

用法

系统资源监控

# 查看帮助
python3 {baseDir}/scripts/monitor.py -h

# 监控所有服务器
python3 {baseDir}/scripts/monitor.py

# 监控指定服务器
python3 {baseDir}/scripts/monitor.py --server prod-01

# JSON格式输出
python3 {baseDir}/scripts/monitor.py --format json

# 表格格式输出
python3 {baseDir}/scripts/monitor.py --format table

# 输出到文件
python3 {baseDir}/scripts/monitor.py --output report.json

网站状态检查

# 查看帮助
python3 {baseDir}/scripts/sites.py -h

# 检查所有服务器的网站状态
python3 {baseDir}/scripts/sites.py

# 检查指定服务器
python3 {baseDir}/scripts/sites.py --server prod-01

# 只显示停止的网站
python3 {baseDir}/scripts/sites.py --filter stopped

# 只显示SSL即将过期的网站（30天内）
python3 {baseDir}/scripts/sites.py --filter ssl-warning

# 只显示SSL已过期的网站
python3 {baseDir}/scripts/sites.py --filter ssl-expired

# JSON格式输出
python3 {baseDir}/scripts/sites.py --format json

# 输出到文件
python3 {baseDir}/scripts/sites.py --output sites.json

服务状态检查

# 查看帮助
python3 {baseDir}/scripts/services.py -h

# 检查所有服务器的服务状态
python3 {baseDir}/scripts/services.py

# 检查指定服务器
python3 {baseDir}/scripts/services.py --server prod-01

# 只检查特定服务
python3 {baseDir}/scripts/services.py --service nginx --service redis

# JSON格式输出
python3 {baseDir}/scripts/services.py --format json

# 输出到文件
python3 {baseDir}/scripts/services.py --output services.json

日志读取

# 查看帮助
python3 {baseDir}/scripts/logs.py -h

# 查看Nginx错误日志
python3 {baseDir}/scripts/logs.py --service nginx

# 查看Redis日志
python3 {baseDir}/scripts/logs.py --service redis

# 查看Apache错误日志
python3 {baseDir}/scripts/logs.py --service apache

# 查看MySQL错误日志
python3 {baseDir}/scripts/logs.py --service mysql

# 查看MySQL慢查询日志
python3 {baseDir}/scripts/logs.py --service mysql --log-type slow

# 查看PostgreSQL日志（需要插件）
python3 {baseDir}/scripts/logs.py --service pgsql

# 查看PostgreSQL慢日志
python3 {baseDir}/scripts/logs.py --service pgsql --log-type slow

# 指定服务器和行数
python3 {baseDir}/scripts/logs.py --server prod-01 --service nginx --lines 200

# JSON格式输出
python3 {baseDir}/scripts/logs.py --service nginx --format json

SSH状态和日志检查

# 查看帮助
python3 {baseDir}/scripts/ssh.py -h

# 查看SSH服务状态
python3 {baseDir}/scripts/ssh.py --status

# 查看SSH登录日志
python3 {baseDir}/scripts/ssh.py --logs

# 只查看失败的登录日志
python3 {baseDir}/scripts/ssh.py --logs --filter failed

# 只查看成功的登录日志
python3 {baseDir}/scripts/ssh.py --logs --filter success

# 搜索特定IP的登录记录
python3 {baseDir}/scripts/ssh.py --logs --search 192.168.1.1

# 指定服务器
python3 {baseDir}/scripts/ssh.py --status --server prod-01

# JSON格式输出
python3 {baseDir}/scripts/ssh.py --logs --format json

计划任务检查

# 查看帮助
python3 {baseDir}/scripts/crontab.py -h

# 查看所有计划任务
python3 {baseDir}/scripts/crontab.py

# 只查看备份任务
python3 {baseDir}/scripts/crontab.py --backup-only

# 查看指定服务器
python3 {baseDir}/scripts/crontab.py --server prod-01

# 查看备份任务日志
python3 {baseDir}/scripts/crontab.py --logs --task-id 11

# JSON格式输出
python3 {baseDir}/scripts/crontab.py --format json

参数说明

monitor.py 参数

参数	说明	默认值
`--server`, `-s`	指定服务器名称	所有服务器
`--format`, `-f`	输出格式 (json/table)	json
`--output`, `-o`	输出文件路径	标准输出
`--config`, `-c`	配置文件路径	自动查找

sites.py 参数

参数	说明	默认值
`--server`, `-s`	指定服务器名称	所有服务器
`--format`, `-f`	输出格式 (json/table)	table
`--output`, `-o`	输出文件路径	标准输出
`--filter`	过滤条件 (stopped/ssl-warning/ssl-expired)	无
`--config`, `-c`	配置文件路径	自动查找

services.py 参数

参数	说明	默认值
`--server`, `-s`	指定服务器名称	所有服务器
`--format`, `-f`	输出格式 (json/table)	table
`--output`, `-o`	输出文件路径	标准输出
`--service`	指定要检查的服务（可多次指定）	默认服务列表
`--config`, `-c`	配置文件路径	自动查找

logs.py 参数

参数	说明	默认值
`--server`, `-s`	指定服务器名称	所有服务器
`--service`	服务名称 (nginx/apache/redis/mysql/pgsql)	必填
`--log-type`	日志类型 (error/slow)	error
`--lines`, `-n`	返回最后N行日志	100
`--format`, `-f`	输出格式 (json/table)	table
`--output`, `-o`	输出文件路径	标准输出
`--config`, `-c`	配置文件路径	自动查找

注意：只有已安装的服务才能获取日志，尝试获取未安装服务的日志会返回错误。

ssh.py 参数

参数	说明	默认值
`--server`, `-s`	指定服务器名称	所有服务器
`--status`	查看SSH服务状态	否
`--logs`	查看SSH登录日志	否
`--filter`	日志过滤 (ALL/success/failed)	ALL
`--search`	搜索关键字（IP或用户名）	无
`--limit`, `-n`	返回日志条数	50
`--format`, `-f`	输出格式 (json/table)	table
`--output`, `-o`	输出文件路径	标准输出
`--config`, `-c`	配置文件路径	自动查找

crontab.py 参数

参数	说明	默认值
`--server`, `-s`	指定服务器名称	所有服务器
`--backup-only`	只显示备份任务	否
`--logs`	查看任务日志	否
`--task-id`	任务ID（配合--logs使用）	无
`--days`	日志查询天数	7
`--format`, `-f`	输出格式 (json/table)	table
`--output`, `-o`	输出文件路径	标准输出
`--config`, `-c`	配置文件路径	自动查找

监控指标

系统资源监控 (monitor.py)

通过单一API接口获取完整的系统监控数据：

CPU: 使用率、核心数、型号、用户/系统占用
内存: 总量、使用量、可用量、缓存、使用率
磁盘: 多分区详情、总量、使用量、使用率
网络: 实时速度、总流量、各网卡统计
负载: 1/5/15分钟负载
系统: 主机名、操作系统、运行时间、面板版本
资源: 网站、数据库、FTP账户数量

网站状态检查 (sites.py)

支持多种项目类型：

类型	进程信息	运行状态判断
PHP	无	status==1 && stop为空
Java	pid_info	pid > 0
Node	load_info	run==true
Go	load_info	run==true
Python	pids	run==true
.NET	load_info	run==true
Proxy(反代)	无	status==1
HTML(静态)	无	status==1
Other(其他)	load_info	run==true

检查项目：

运行状态: 运行中/已停止/启动中
SSL证书: 有效/即将过期/已过期
进程信息: PID、内存、CPU、线程数（适用于Java/Node/Go/Python/.NET/Other）
反代健康: 反代项目的后端健康状态
基础信息: 路径、域名、PHP版本、端口、代理地址

服务状态检查 (services.py)

支持检查的服务：

服务	状态检查	日志支持
Nginx	✓	✓ 错误日志
Apache	✓	✓ 错误日志
MySQL	✓	✓ 错误日志/慢日志
Redis	✓	✓ 日志文件
Memcached	✓	✗
Pure-FTPD	✓	✗
PHP (多版本)	✓	✗
PostgreSQL	✓	✓ 错误日志/慢日志

服务状态字段说明：

字段	说明
`installed` (setup)	服务是否已安装
`status`	服务是否正在运行
`version`	已安装的版本号
`pid`	主进程ID（运行中时）

重要区别：

installed=false：服务未安装，无法获取日志
installed=true, status=false：服务已安装但未运行
installed=true, status=true：服务已安装且正在运行

PHP多版本共存说明：

PHP是支持多版本共存的服务，一台服务器可能同时安装多个PHP版本
PHP服务名称格式：php-X.X（如 php-8.2、php-7.4）
系统会自动扫描已安装的PHP版本并分别显示状态
常见PHP版本：8.5, 8.4, 8.3, 8.2, 8.1, 8.0, 7.4, 7.3, 7.2, 7.1, 7.0, 5.4, 5.3, 5.2

检查项目：

运行状态: 运行中/已停止
版本信息: 已安装版本号
进程PID: 主进程ID

日志读取 (logs.py)

支持的日志类型：

日志类型	服务	获取方式
错误日志	nginx	文件: /www/server/nginx/logs/error.log
错误日志	apache	文件: /www/wwwlogs/error_log
日志文件	redis	文件: /www/server/redis/redis.log
错误日志	mysql	接口: /database?action=GetErrorLog
慢日志	mysql	接口: /database?action=GetSlowLogs
错误日志	pgsql	插件接口: pgsql_manager
慢日志	pgsql	插件接口: pgsql_manager

注意事项：

只有已安装（installed=true）的服务才能获取日志
尝试获取未安装服务的日志会返回错误
Memcached 和 Pure-FTPD 不支持日志获取

SSH状态和日志检查 (ssh.py)

检查项目：

SSH服务状态: 运行中/已停止
端口: SSH监听端口
Ping设置: 是否允许ping
防火墙状态: 是否启用
Fail2ban: 是否安装和运行

登录日志字段：

时间: 登录时间
类型: 成功/失败
用户: 登录用户名
IP地址: 来源IP
地区: IP归属地
登录方式: password/key

计划任务检查 (crontab.py)

任务类型：

备份网站: 自动备份网站文件和数据库
备份数据库: 单独备份数据库
备份目录: 备份指定目录
Shell脚本: 自定义Shell命令
同步时间: NTP时间同步
切割日志: 日志分割任务
访问URL: 定时HTTP请求

检查项目：

任务状态: 启用/禁用
执行周期: 每天/每小时/每周/每月/间隔分钟
备份目标: 网站名称/数据库名称
保留数量: 备份保留份数
执行结果: 最后一次执行状态

告警配置

SSL证书告警

剩余天数	告警级别
已过期	critical
≤ 7 天	critical
≤ 30 天	warning

服务器资源告警阈值

可在配置文件中设置告警阈值：

global:
  thresholds:
    cpu: 80      # CPU使用率告警阈值(%)
    memory: 85   # 内存使用率告警阈值(%)
    disk: 90     # 磁盘使用率告警阈值(%)

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/btpanel/SKILL.md

View on GitHub ↗

License MITImported 8/2/2026Version v1Bundled 7 files · scripts

Illustrative Want to see what leoyeai/btpanel 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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图标资源

AI 使用约束

服务器配置管理

常用场景

场景一：初次使用配置服务器

场景二：多服务器资源汇总

场景三：单台服务器日常巡检

场景四：网站SSL证书检查

场景五：安全审计

场景六：服务故障排查

场景七：备份任务检查

版本要求

用法

系统资源监控

网站状态检查

服务状态检查

日志读取

SSH状态和日志检查

计划任务检查

参数说明

monitor.py 参数

sites.py 参数

services.py 参数

logs.py 参数

ssh.py 参数

crontab.py 参数

监控指标

系统资源监控 (monitor.py)

网站状态检查 (sites.py)

服务状态检查 (services.py)

日志读取 (logs.py)

SSH状态和日志检查 (ssh.py)

计划任务检查 (crontab.py)

告警配置

SSL证书告警

服务器资源告警阈值

SkillSafety

Source

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