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Cloudcc Openapi Withobject · leoyeai | DecimalAI

Sales & Supportby leoyeai

Cloudcc Openapi Withobject

CloudCC OpenAPI 调用技能 - 提供完整的 REST API 接口调用能力，支持对象/字段元数据查询

Never made a case worse

SkillScore

SkillScore99/100

Test results 100 · Live runs 99

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

25%100%of test cases passed +75 pts

Without skill6 of 24

With skill24 of 24

18 fixed6 passed either way0 still failing0 broke

Measured on gemini-3.6-flash8/6/2026v1

Track record

Agent runs: 119; 37 in the last 30 days

See one task, with and without the skill

One test taskWhat API path and HTTP verb are used in CloudCC OpenAPI to download a stored file resource?

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-cloudcc-openapi-withobject
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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject/SKILL.md https://app.decimal.ai/s/leoyeai-cloudcc-openapi-withobject/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/leoyeai-cloudcc-openapi-withobject/SKILL.md

This gets SKILL.md only. The skill's 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject/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-cloudcc-openapi-withobject/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 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/leoyeai-cloudcc-openapi-withobject/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 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/leoyeai-cloudcc-openapi-withobject/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 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/leoyeai-cloudcc-openapi-withobject/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 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject/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-cloudcc-openapi-withobject/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 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/leoyeai-cloudcc-openapi-withobject/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 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject/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 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/leoyeai-cloudcc-openapi-withobject/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 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/leoyeai-cloudcc-openapi-withobject/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 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/leoyeai-cloudcc-openapi-withobject/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 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/leoyeai-cloudcc-openapi-withobject/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 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject")
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-cloudcc-openapi-withobject/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/leoyeai-cloudcc-openapi-withobject/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 6 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-cloudcc-openapi-withobject

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-cloudcc-openapi-withobject/SKILL.md https://app.decimal.ai/s/leoyeai-cloudcc-openapi-withobject/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/leoyeai-cloudcc-openapi-withobject/SKILL.md

This gets SKILL.md only. The skill's 6 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-cloudcc-openapi-withobject/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/leoyeai-cloudcc-openapi-withobject.json

This gets SKILL.md only. The skill's 6 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

技能信息

名称: cloudcc-openapi-withobject
版本: 2.0.0
作者: 鲁班
创建日期: 2026-03-20
更新日期: 2026-03-20
适用范围: CloudCC One 版本 OpenAPI 接口调用

安装配置

配置参数

参数	说明	默认值	必填
`orgId`	组织 ID	-	是
`username`	登录用户名	-	是
`safetyMark`	安全标记（邮箱获取）	-	是
`clientId`	连接应用的 clientId	-	是
`secretKey`	连接应用的 secretKey	-	是
`apiDomain`	API 网关地址（动态获取）	-	否（自动获取）

获取配置信息

组织 ID (orgId): 系统设置 - 公司信息中查看
安全标记 (safetyMark): 个人信息 - 重置我的安全标记（发送到邮箱）
clientId/secretKey: 管理设置 - 安全性控制 - 连接的应用程序

安装步骤

# 1. 创建技能目录
mkdir -p ~/.openclaw/skills/cloudcc-openapi-withobject

# 2. 创建配置文件
cat > ~/.openclaw/skills/cloudcc-openapi-withobject/config.json << 'EOF'
{
  "orgId": "your-org-id",
  "username": "your-username",
  "safetyMark": "your-safety-mark",
  "clientId": "your-client-id",
  "secretKey": "your-secret-key"
}
EOF

核心功能

1. 认证管理

动态获取组织 API 网关地址
获取 accessToken 并自动刷新
accessToken 有效性验证
认证事件日志记录

2. 元数据查询（新增 v2.0.0）

方法	说明	API 端点
`getAllTabs`	获取所有选项卡（推荐用于查找对象）	`/openApi/common` (getAllTabs)
`pageQuery`	查询对象数据（不带 fields 返回所有字段）	`/openApi/common` (pageQuery)
`getStandardObjects`	获取标准对象列表	`/api/customObject/standardObjList`
`getCustomObjects`	获取自定义对象列表	`/api/customObject/list`
`getObjectFields`	获取对象字段列表	`/api/fieldSetup/queryField`

注意: 元数据查询 API (/api/customObject/* 和 /api/fieldSetup/*) 可能需要额外的权限或使用 Setup 服务域名。推荐使用 getAllTabs 方法查找对象 API 名称。

3. 数据操作

查询: 普通查询、分页查询、带权限查询、SQL 查询
插入: 普通插入、带权限插入
更新: 普通更新、带权限更新
删除: 普通删除、带权限删除
Upsert: 插入或更新

4. 文件服务

图片上传（单张/多张）
文件上传（流/base64）
文件下载
附件管理

5. 消息服务

发送邮件
发送手机短信
Chatter 微帖操作

6. 审批流程

查询待审批项目
批准/拒绝/重新分配
提交审批

7. 安全日志（v2.1.0 新增）

自动记录所有 API 调用（服务名、对象、响应码、耗时）
记录认证事件（token 请求、刷新、过期）
日志自动清理（保留最近 3 天）
支持日志查询、统计、导出

使用方法

快速开始

# 1. 获取 API 网关地址
curl -X GET "https://developer.apis.cloudcc.cn/oauth/apidomain?scope=cloudccCRM&orgId=YOUR_ORG_ID"

# 返回示例:
# {"result":true,"returnInfo":"","returnCode":"1","orgapi_address":"https://xxxx.apis.cloudcc.cn/lightningapi"}

# 2. 获取 accessToken
curl -X POST "https://xxxx.apis.cloudcc.cn/lightningapi/api/cauth/token" \
  -H "Content-Type: application/json" \
  -d '{
    "username":"your-username",
    "safetyMark":"your-safety-mark",
    "clientId":"your-client-id",
    "secretKey":"your-secret-key",
    "orgId":"your-org-id",
    "grant_type":"password"
  }'

# 返回示例:
# {"data":{"accessToken":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9..."},"returnCode":"1","result":true}

日志管理（v2.1.0 新增）

# 查看最近的日志
~/.openclaw/skills/cloudcc-openapi-withobject/scripts/logger.sh view 50

# 查看统计信息
~/.openclaw/skills/cloudcc-openapi-withobject/scripts/logger.sh stats 3

# 搜索日志
~/.openclaw/skills/cloudcc-openapi-withobject/scripts/logger.sh search "productuplist"

# 导出日志
~/.openclaw/skills/cloudcc-openapi-withobject/scripts/logger.sh export

# 清理旧日志（保留最近 3 天）
~/.openclaw/skills/cloudcc-openapi-withobject/scripts/logger.sh cleanup 3

日志格式

每条日志为 JSON 格式，包含以下字段：

{
  "timestamp": "2026-03-20 12:15:30",
  "type": "API_REQUEST",
  "service": "pageQuery",
  "objectApi": "productuplist",
  "responseCode": "1",
  "durationMs": "125"
}

日志类型

类型	说明	示例
`API_REQUEST`	API 调用记录	记录所有 OpenAPI 调用
`AUTH_EVENT`	认证事件	token 请求、刷新、过期

元数据查询示例（v2.0.0 新增）

获取标准对象列表

curl -X POST "$API_DOMAIN/api/customObject/standardObjList" \
  -H "accessToken: $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{}'

返回示例:

{
  "result": true,
  "data": [
    {"id": "account", "objname": "客户", "label": "Account", "objprefix": "001"},
    {"id": "contact", "objname": "联系人", "label": "Contact", "objprefix": "003"},
    {"id": "opportunity", "objname": "业务机会", "label": "Opportunity", "objprefix": "002"}
  ]
}

获取自定义对象列表

curl -X POST "$API_DOMAIN/api/customObject/list" \
  -H "accessToken: $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"id":""}'

返回示例:

{
  "result": true,
  "data": {
    "objList": [
      {"id": "2021A51AA0D3785lBzwh", "objLabel": "产品需求研发报备记录", "schemetable_name": "productuplist", "prefix": "b70"},
      {"id": "2023D181015EDF0f7G1y", "objLabel": "需求池", "schemetable_name": "requirementpool", "prefix": "c75"}
    ]
  }
}

获取对象字段列表

curl -X POST "$API_DOMAIN/api/fieldSetup/queryField" \
  -H "accessToken: $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"prefix":"b70"}'

返回示例:

{
  "result": true,
  "data": {
    "obj": {"id": "2021A51AA0D3785lBzwh", "label": "产品需求研发报备记录"},
    "stdFields": [
      {"id": "1", "labelName": "名称", "schemefieldName": "name", "schemefieldType": "S"}
    ],
    "cusFields": [
      {"id": "c1", "labelName": "产品", "schemefieldName": "product", "schemefieldType": "S"},
      {"id": "c2", "labelName": "状态", "schemefieldName": "zhuangtai", "schemefieldType": "L"}
    ]
  }
}

通过选项卡查找对象（实用技巧）

# 搜索包含关键词的选项卡
curl -X POST "$API_DOMAIN/openApi/common" \
  -H "accessToken: $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"serviceName":"getAllTabs"}' | jq '.data[] | select(.tab_name | test("产品 | 需求"))'

返回示例:

{
  "tab_name": "产品需求研发报备记录",
  "objectApi": "productuplist",
  "prefix": "b70",
  "objId": "2021A51AA0D3785lBzwh"
}

数据查询示例

普通查询 (cquery)

{
  "serviceName": "cquery",
  "objectApiName": "Contact",
  "expressions": "name='test'",
  "isAddDelete": "false",
  "fields": "name,createdate,createbyid"
}

分页查询 (pageQuery)

{
  "serviceName": "pageQuery",
  "objectApiName": "Account",
  "fields": "id,name,phone",
  "expressions": "industry='Technology'",
  "pageNUM": 1,
  "pageSize": 20
}

插入数据 (insert)

{
  "serviceName": "insert",
  "objectApiName": "Contact",
  "data": "[{\"name\":\"张三\",\"phone\":\"13800138000\",\"email\":\"[email protected]\"}]"
}

更新数据 (update)

{
  "serviceName": "update",
  "objectApiName": "Contact",
  "data": "[{\"id\":\"003202100BDF459HcI1R\",\"name\":\"李四\",\"phone\":\"13900139000\"}]"
}

删除数据 (delete)

{
  "serviceName": "delete",
  "objectApiName": "Contact",
  "data": "[{\"id\":\"003202100BDF459HcI1R\"}]"
}

Upsert (插入或更新)

{
  "serviceName": "upsert",
  "objectApiName": "Contact",
  "data": "[{\"id\":\"003202100BDF459HcI1R\",\"name\":\"王五\"}]"
}

API 接口列表

认证相关

接口	服务名	说明
获取网关	GET /oauth/apidomain	动态获取组织 API 地址
获取 token	POST /api/cauth/token	获取 accessToken
验证 token	isValidWithBinding	验证 accessToken 有效性

元数据查询（v2.0.0 新增）

接口	端点	说明
获取标准对象	POST /api/customObject/standardObjList	返回所有标准对象
获取自定义对象	POST /api/customObject/list	返回所有自定义对象
获取对象字段	POST /api/fieldSetup/queryField	根据 prefix 查询字段
获取选项卡	POST /openApi/common (getAllTabs)	返回所有选项卡配置

查询服务

接口	服务名	说明
普通查询	cquery	基础查询
带权限查询	cqueryWithRoleRight	含权限控制的查询
分页查询	pageQuery	分页数据查询
分页带权限查询	pageQueryWithRoleRight	含权限的分页查询
获取查询权限	getQueryPermisson	获取对象查询权限
SQL 查询	cqlQueryWithLogInfo	自定义 SQL 查询
静态查询	cqlQueryWithStatic	支持游标的静态查询

数据操作

接口	服务名	说明
插入	insert	插入数据
带权限插入	insertWithRoleRight	含权限控制的插入
更新	update	更新数据
带权限更新	updateWithRoleRight	含权限控制的更新
删除	delete	删除数据
带权限删除	deleteWithRoleRight	含权限控制的删除
Upsert	upsert	插入或更新
Upsert 带权限	upsertWithRoleRight	含权限的 upsert

文件服务

接口	服务名	地址	说明
上传图片	uploadImg	/openApi/file	单张图片上传
上传多图	uploadImgMany	/openApi/file	最多 9 张
获取图片属性	getImgProperty	/openApi/common	查询图片信息
上传文件	uploadFile	/openApi/file	文件流上传
上传附件	uploadAttachement	/openApi/common	base64 上传
下载文件	downloadFile	/openApi/downloadFile	GET 请求
下载附件	downloadAttachement	/openApi/common	base64 下载
删除附件	deleteAttachment	/openApi/common	删除附件
删除文件	deleteFile	/openApi/common	删除文件

消息服务

接口	服务名	说明
发送邮件	sendEmail	支持模板变量
发送短信	telMessage	手机消息服务

Chatter 服务

接口	服务名	说明
获取 Chatter	getChatters01	查询微帖内容
获取我的 Chatter	getMyChatter01	我追随的内容
获取追随者	getFollowUsers	查询追随关系
发布帖子	addMicroPostF	普通帖子
发布文件帖	addMicroPostD	带文件的帖子
发布链接帖	addMicroPostL	带链接的帖子
发布投票帖	addMicroPostV	投票类型帖子
投票	voteMicroPost	对帖子投票
发布评论	addMicroComment	普通评论
文件评论	addMicroCommentFile	带文件评论
点赞帖子	praiseFeed	喜欢/取消喜欢
点赞评论	praiseComment	评论点赞
收藏帖子	favoriteFeed	收藏/取消收藏
删除帖子	removeMicroPost	删除微帖
删除评论	removeMicroComment	删除评论
追随操作	operateFollowRelation	追随/取消追随

审批服务

接口	服务名	说明
待审批列表	getApprovalPaddingList	查询待审批项目
批准	doApproved	批准操作
拒绝	doRejected	拒绝操作
重新分配	doReassign	重新分配审批人
调回	reCall	调回审批
提交审批	submitForApproval	提交审批流程

其他服务

接口	服务名	说明
获取应用列表	getAppList	应用程序列表
获取选项卡	getAllTabs	选项卡信息
获取应用和选项卡	getAppAndTabList	合并查询
获取搜索设置	getMySetupObjs	搜索配置
获取选项列表值	getPickListValue	字段选项值
保存依赖关系	saveDependency	选项依赖配置
自助服务	customService	MongoDB 数据操作

返回码说明

代码	说明
1	调用成功
-1	调用成功但接口异常
-2	调用不成功（如失效）
-3	参数输入有误

最佳实践

1. 查找对象的完整流程（v2.0.0）

# 步骤 1: 通过选项卡名称查找对象（最直观）
curl -X POST "$API_DOMAIN/openApi/common" \
  -H "accessToken: $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"serviceName":"getAllTabs"}' | jq '.data[] | select(.tab_name | test("产品需求"))'

# 返回：{"objectApi":"productuplist","prefix":"b70","objId":"2021A51AA0D3785lBzwh"}

# 步骤 2: 使用 objectApi 查询数据
curl -X POST "$API_DOMAIN/openApi/common" \
  -H "accessToken: $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"serviceName":"pageQuery","objectApiName":"productuplist","pageNUM":1,"pageSize":20}'

# 步骤 3: 使用 prefix 查询字段结构
curl -X POST "$API_DOMAIN/api/fieldSetup/queryField" \
  -H "accessToken: $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"prefix":"b70"}'

2. 网关地址动态获取

禁止写死 API 地址，组织网关可能根据负载漂移：

# 每次启动时获取
API_DOMAIN=$(curl -s "https://developer.apis.cloudcc.cn/oauth/apidomain?scope=cloudccCRM&orgId=$ORG_ID" | jq -r '.orgapi_address')

3. accessToken 管理

accessToken 放入请求头：accessToken: <value>
定期验证有效性（使用 isValidWithBinding）
失效时重新获取

4. 批量操作

插入/更新/删除支持批量操作
data 参数为 JSON 数组：[{...}, {...}]
注意 API 调用配额限制

5. 特殊字符处理

URL 中的特殊字符需要 URL 编码：

java.net.URLEncoder.encode("%", "UTF-8")

6. 字段命名规范

服务名和参数名首字母小写
如文档中大写，请改为小写

API 配额限制

版本	基础次数	每用户额外	最大限额/24h
专业版	5000	用户数×150	10000
企业版	50000	用户数×300	200000
旗舰版	50000	用户数×500	500000
超级版	50000	用户数×500	500000

⚠️ 禁止超负荷请求，否则 API Client 可能被停用

故障排查

常见问题

accessToken 失效: 重新调用 /api/cauth/token
网关地址变化: 重新获取 /oauth/apidomain
权限不足: 检查简档权限或使用带权限接口
参数错误: 检查字段名是否小写、JSON 格式是否正确
对象不存在: 使用 getAllTabs 或 getCustomObjects 确认对象 API 名称

调试技巧

# 1. 验证 token 有效性
curl -X POST "$API_DOMAIN/openApi/common" \
  -H "accessToken: $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"serviceName":"isValidWithBinding"}'

# 2. 检查返回码
# returnCode: "1" 表示成功
# returnCode: "-1" 表示接口异常
# returnCode: "-2" 表示 token 失效
# returnCode: "-3" 表示参数错误

# 3. 查找对象 API 名称
curl -X POST "$API_DOMAIN/openApi/common" \
  -H "accessToken: $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"serviceName":"getAllTabs"}' | jq '.data[] | select(.tab_name | test("关键词"))'

版本历史

v2.1.0 (2026-03-20)

✅ 新增安全日志功能
✅ 支持 logger.sh - 日志管理工具
✅ 自动记录所有 API 调用（服务名、对象、响应码、耗时）
✅ 自动记录认证事件（token 请求、刷新、过期）
✅ 日志自动清理（保留最近 3 天）
✅ 支持日志查询、统计、导出

v2.0.0 (2026-03-20)

✅ 新增元数据查询能力
✅ 支持 getStandardObjects - 获取标准对象列表
✅ 支持 getCustomObjects - 获取自定义对象列表
✅ 支持 getObjectFields - 获取对象字段列表
✅ 支持 getAllTabs - 获取选项卡信息
✅ 新增对象查找最佳实践文档

v1.0.0 (2026-03-20)

✅ 初始版本
✅ 完整 API 接口文档
✅ 认证管理
✅ 数据 CRUD 操作
✅ 文件服务
✅ 消息服务
✅ Chatter 接口
✅ 审批流程

维护人: 鲁班
参考文档: https://help.cloudcc.cn/product03/apigai-lan/

About this skill

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✓ 3 of 3 passed

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Source

Imported

LeoYeAI / openclaw-master-skills

skills/cloudcc-openapi-withobject/SKILL.md

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License MITImported 8/2/2026Version v1Bundled 6 files · scripts

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What it changes

Track record

Use this skill

技能信息

安装配置

配置参数

获取配置信息

安装步骤

核心功能

1. 认证管理

2. 元数据查询（新增 v2.0.0）

3. 数据操作

4. 文件服务

5. 消息服务

6. 审批流程

7. 安全日志（v2.1.0 新增）

使用方法

快速开始

日志管理（v2.1.0 新增）

日志格式

日志类型

元数据查询示例（v2.0.0 新增）

获取标准对象列表

获取自定义对象列表

获取对象字段列表

通过选项卡查找对象（实用技巧）

数据查询示例

普通查询 (cquery)

分页查询 (pageQuery)

插入数据 (insert)

更新数据 (update)

删除数据 (delete)

Upsert (插入或更新)

API 接口列表

认证相关

元数据查询（v2.0.0 新增）

查询服务

数据操作

文件服务

消息服务

Chatter 服务

审批服务

其他服务

返回码说明

最佳实践

1. 查找对象的完整流程（v2.0.0）

2. 网关地址动态获取

3. accessToken 管理

4. 批量操作

5. 特殊字符处理

6. 字段命名规范

API 配额限制

故障排查

常见问题

调试技巧

版本历史

v2.1.0 (2026-03-20)

v2.0.0 (2026-03-20)

v1.0.0 (2026-03-20)

SkillSafety

Source

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