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DOCX creation, editing, and analysis · leoyeai | DecimalAI

Documentationby leoyeai

DOCX creation, editing, and analysis

Word 文档处理 | Word Document Processing. 创建、读取、编辑 Word 文档 | Create, read, edit Word documents. 支持 .docx 格式、格式化、表格、图片 | Supports .docx format, formatting, tables, images. 触发词：Word、文档、docx.

SkillScore

SkillScore91/100

Test results 91

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

45%91%of test cases passed +45 pts

Without skill10 of 22

With skill20 of 22

10 fixed10 passed either way2 still failing0 broke

Measured on gemini-3.6-flash8/10/2026v120 comparable

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskI want to unpack a docx file named 'report.docx' into the 'unpacked/' directory, but I want to skip merging adjacent runs. What command should I run?

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-docx-cn
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-docx-cn")
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-docx-cn

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

Copy SKILL.md

Save it in your project, as

.claude/skills/leoyeai-docx-cn/SKILL.md

This gets SKILL.md only. The skill's 3 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-docx-cn

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-docx-cn")
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-docx-cn/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-docx-cn/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 3 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-docx-cn

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-docx-cn")
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-docx-cn/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/leoyeai-docx-cn/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 3 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-docx-cn

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-docx-cn")
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-docx-cn/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/leoyeai-docx-cn/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 3 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-docx-cn

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-docx-cn")
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-docx-cn/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/leoyeai-docx-cn/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 3 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-docx-cn

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-docx-cn")
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-docx-cn/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-docx-cn/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 3 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-docx-cn

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-docx-cn")
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-docx-cn/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/leoyeai-docx-cn/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 3 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-docx-cn

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-docx-cn")
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-docx-cn/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 3 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-docx-cn

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-docx-cn")
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-docx-cn/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/leoyeai-docx-cn/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 3 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-docx-cn

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-docx-cn")
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-docx-cn/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/leoyeai-docx-cn/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 3 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-docx-cn

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-docx-cn")
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-docx-cn/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/leoyeai-docx-cn/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 3 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-docx-cn

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-docx-cn")
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-docx-cn/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/leoyeai-docx-cn/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 3 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-docx-cn

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-docx-cn")
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-docx-cn/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/leoyeai-docx-cn/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 3 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-docx-cn

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

Copy SKILL.md

Save it in your project, as

.agents/skills/leoyeai-docx-cn/SKILL.md

This gets SKILL.md only. The skill's 3 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-docx-cn/SKILL.md

Read the summary as JSON

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

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 8/10/2026
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

DOCX creation, editing, and analysis

Overview

A .docx file is a ZIP archive containing XML files.

Quick Reference

Task	Approach
Read/analyze content	`pandoc` or unpack for raw XML
Create new document	Use `docx-js` - see Creating New Documents below
Edit existing document	Unpack → edit XML → repack - see Editing Existing Documents below

Converting .doc to .docx

Legacy .doc files must be converted before editing:

python scripts/office/soffice.py --headless --convert-to docx document.doc

Reading Content

# Text extraction with tracked changes
pandoc --track-changes=all document.docx -o output.md

# Raw XML access
python scripts/office/unpack.py document.docx unpacked/

Converting to Images

python scripts/office/soffice.py --headless --convert-to pdf document.docx
pdftoppm -jpeg -r 150 document.pdf page

Accepting Tracked Changes

To produce a clean document with all tracked changes accepted (requires LibreOffice):

python scripts/accept_changes.py input.docx output.docx

Creating New Documents

Generate .docx files with JavaScript, then validate. Install: npm install -g docx

Setup

const { Document, Packer, Paragraph, TextRun, Table, TableRow, TableCell, ImageRun,
        Header, Footer, AlignmentType, PageOrientation, LevelFormat, ExternalHyperlink,
        TableOfContents, HeadingLevel, BorderStyle, WidthType, ShadingType,
        VerticalAlign, PageNumber, PageBreak } = require('docx');

const doc = new Document({ sections: [{ children: [/* content */] }] });
Packer.toBuffer(doc).then(buffer => fs.writeFileSync("doc.docx", buffer));

Validation

After creating the file, validate it. If validation fails, unpack, fix the XML, and repack.

python scripts/office/validate.py doc.docx

Page Size

// CRITICAL: docx-js defaults to A4, not US Letter
// Always set page size explicitly for consistent results
sections: [{
  properties: {
    page: {
      size: {
        width: 12240,   // 8.5 inches in DXA
        height: 15840   // 11 inches in DXA
      },
      margin: { top: 1440, right: 1440, bottom: 1440, left: 1440 } // 1 inch margins
    }
  },
  children: [/* content */]
}]

Common page sizes (DXA units, 1440 DXA = 1 inch):

Paper	Width	Height	Content Width (1" margins)
US Letter	12,240	15,840	9,360
A4 (default)	11,906	16,838	9,026

Landscape orientation: docx-js swaps width/height internally, so pass portrait dimensions and let it handle the swap:

size: {
  width: 12240,   // Pass SHORT edge as width
  height: 15840,  // Pass LONG edge as height
  orientation: PageOrientation.LANDSCAPE  // docx-js swaps them in the XML
},
// Content width = 15840 - left margin - right margin (uses the long edge)

Styles (Override Built-in Headings)

Use Arial as the default font (universally supported). Keep titles black for readability.

const doc = new Document({
  styles: {
    default: { document: { run: { font: "Arial", size: 24 } } }, // 12pt default
    paragraphStyles: [
      // IMPORTANT: Use exact IDs to override built-in styles
      { id: "Heading1", name: "Heading 1", basedOn: "Normal", next: "Normal", quickFormat: true,
        run: { size: 32, bold: true, font: "Arial" },
        paragraph: { spacing: { before: 240, after: 240 }, outlineLevel: 0 } }, // outlineLevel required for TOC
      { id: "Heading2", name: "Heading 2", basedOn: "Normal", next: "Normal", quickFormat: true,
        run: { size: 28, bold: true, font: "Arial" },
        paragraph: { spacing: { before: 180, after: 180 }, outlineLevel: 1 } },
    ]
  },
  sections: [{
    children: [
      new Paragraph({ heading: HeadingLevel.HEADING_1, children: [new TextRun("Title")] }),
    ]
  }]
});

Lists (NEVER use unicode bullets)

// ❌ WRONG - never manually insert bullet characters
new Paragraph({ children: [new TextRun("• Item")] })  // BAD
new Paragraph({ children: [new TextRun("\u2022 Item")] })  // BAD

// ✅ CORRECT - use numbering config with LevelFormat.BULLET
const doc = new Document({
  numbering: {
    config: [
      { reference: "bullets",
        levels: [{ level: 0, format: LevelFormat.BULLET, text: "•", alignment: AlignmentType.LEFT,
          style: { paragraph: { indent: { left: 720, hanging: 360 } } } }] },
      { reference: "numbers",
        levels: [{ level: 0, format: LevelFormat.DECIMAL, text: "%1.", alignment: AlignmentType.LEFT,
          style: { paragraph: { indent: { left: 720, hanging: 360 } } } }] },
    ]
  },
  sections: [{
    children: [
      new Paragraph({ numbering: { reference: "bullets", level: 0 },
        children: [new TextRun("Bullet item")] }),
      new Paragraph({ numbering: { reference: "numbers", level: 0 },
        children: [new TextRun("Numbered item")] }),
    ]
  }]
});

// ⚠️ Each reference creates INDEPENDENT numbering
// Same reference = continues (1,2,3 then 4,5,6)
// Different reference = restarts (1,2,3 then 1,2,3)

Tables

CRITICAL: Tables need dual widths - set both columnWidths on the table AND width on each cell. Without both, tables render incorrectly on some platforms.

// CRITICAL: Always set table width for consistent rendering
// CRITICAL: Use ShadingType.CLEAR (not SOLID) to prevent black backgrounds
const border = { style: BorderStyle.SINGLE, size: 1, color: "CCCCCC" };
const borders = { top: border, bottom: border, left: border, right: border };

new Table({
  width: { size: 9360, type: WidthType.DXA }, // Always use DXA (percentages break in Google Docs)
  columnWidths: [4680, 4680], // Must sum to table width (DXA: 1440 = 1 inch)
  rows: [
    new TableRow({
      children: [
        new TableCell({
          borders,
          width: { size: 4680, type: WidthType.DXA }, // Also set on each cell
          shading: { fill: "D5E8F0", type: ShadingType.CLEAR }, // CLEAR not SOLID
          margins: { top: 80, bottom: 80, left: 120, right: 120 }, // Cell padding (internal, not added to width)
          children: [new Paragraph({ children: [new TextRun("Cell")] })]
        })
      ]
    })
  ]
})

Table width calculation:

Always use WidthType.DXA — WidthType.PERCENTAGE breaks in Google Docs.

// Table width = sum of columnWidths = content width
// US Letter with 1" margins: 12240 - 2880 = 9360 DXA
width: { size: 9360, type: WidthType.DXA },
columnWidths: [7000, 2360]  // Must sum to table width

Width rules:

Always use WidthType.DXA — never WidthType.PERCENTAGE (incompatible with Google Docs)
Table width must equal the sum of columnWidths
Cell width must match corresponding columnWidth
Cell margins are internal padding - they reduce content area, not add to cell width
For full-width tables: use content width (page width minus left and right margins)

Images

// CRITICAL: type parameter is REQUIRED
new Paragraph({
  children: [new ImageRun({
    type: "png", // Required: png, jpg, jpeg, gif, bmp, svg
    data: fs.readFileSync("image.png"),
    transformation: { width: 200, height: 150 },
    altText: { title: "Title", description: "Desc", name: "Name" } // All three required
  })]
})

Page Breaks

// CRITICAL: PageBreak must be inside a Paragraph
new Paragraph({ children: [new PageBreak()] })

// Or use pageBreakBefore
new Paragraph({ pageBreakBefore: true, children: [new TextRun("New page")] })

// CRITICAL: Headings must use HeadingLevel ONLY - no custom styles
new TableOfContents("Table of Contents", { hyperlink: true, headingStyleRange: "1-3" })

Headers/Footers

sections: [{
  properties: {
    page: { margin: { top: 1440, right: 1440, bottom: 1440, left: 1440 } } // 1440 = 1 inch
  },
  headers: {
    default: new Header({ children: [new Paragraph({ children: [new TextRun("Header")] })] })
  },
  footers: {
    default: new Footer({ children: [new Paragraph({
      children: [new TextRun("Page "), new TextRun({ children: [PageNumber.CURRENT] })]
    })] })
  },
  children: [/* content */]
}]

Critical Rules for docx-js

Set page size explicitly - docx-js defaults to A4; use US Letter (12240 x 15840 DXA) for US documents
Landscape: pass portrait dimensions - docx-js swaps width/height internally; pass short edge as width, long edge as height, and set orientation: PageOrientation.LANDSCAPE
Never use \n - use separate Paragraph elements
Never use unicode bullets - use LevelFormat.BULLET with numbering config
PageBreak must be in Paragraph - standalone creates invalid XML
ImageRun requires type - always specify png/jpg/etc
Always set table width with DXA - never use WidthType.PERCENTAGE (breaks in Google Docs)
Tables need dual widths - columnWidths array AND cell width, both must match
Table width = sum of columnWidths - for DXA, ensure they add up exactly
Always add cell margins - use margins: { top: 80, bottom: 80, left: 120, right: 120 } for readable padding
Use ShadingType.CLEAR - never SOLID for table shading
TOC requires HeadingLevel only - no custom styles on heading paragraphs
Override built-in styles - use exact IDs: "Heading1", "Heading2", etc.
Include outlineLevel - required for TOC (0 for H1, 1 for H2, etc.)

Editing Existing Documents

Follow all 3 steps in order.

Step 1: Unpack

python scripts/office/unpack.py document.docx unpacked/

Extracts XML, pretty-prints, merges adjacent runs, and converts smart quotes to XML entities (“ etc.) so they survive editing. Use --merge-runs false to skip run merging.

Step 2: Edit XML

Edit files in unpacked/word/. See XML Reference below for patterns.

Use "Claude" as the author for tracked changes and comments, unless the user explicitly requests use of a different name.

Use the Edit tool directly for string replacement. Do not write Python scripts. Scripts introduce unnecessary complexity. The Edit tool shows exactly what is being replaced.

CRITICAL: Use smart quotes for new content. When adding text with apostrophes or quotes, use XML entities to produce smart quotes:

<!-- Use these entities for professional typography -->
<w:t>Here&#x2019;s a quote: &#x201C;Hello&#x201D;</w:t>

Entity	Character
`‘`	‘ (left single)
`’`	’ (right single / apostrophe)
`“`	“ (left double)
`”`	” (right double)

Adding comments: Use comment.py to handle boilerplate across multiple XML files (text must be pre-escaped XML):

python scripts/comment.py unpacked/ 0 "Comment text with &amp; and &#x2019;"
python scripts/comment.py unpacked/ 1 "Reply text" --parent 0  # reply to comment 0
python scripts/comment.py unpacked/ 0 "Text" --author "Custom Author"  # custom author name

Then add markers to document.xml (see Comments in XML Reference).

Step 3: Pack

python scripts/office/pack.py unpacked/ output.docx --original document.docx

Validates with auto-repair, condenses XML, and creates DOCX. Use --validate false to skip.

Auto-repair will fix:

durableId >= 0x7FFFFFFF (regenerates valid ID)
Missing xml:space="preserve" on <w:t> with whitespace

Auto-repair won't fix:

Malformed XML, invalid element nesting, missing relationships, schema violations

Common Pitfalls

Replace entire <w:r> elements: When adding tracked changes, replace the whole <w:r>...</w:r> block with <w:del>...<w:ins>... as siblings. Don't inject tracked change tags inside a run.
Preserve <w:rPr> formatting: Copy the original run's <w:rPr> block into your tracked change runs to maintain bold, font size, etc.

XML Reference

Schema Compliance

Element order in <w:pPr>: <w:pStyle>, <w:numPr>, <w:spacing>, <w:ind>, <w:jc>, <w:rPr> last
Whitespace: Add xml:space="preserve" to <w:t> with leading/trailing spaces
RSIDs: Must be 8-digit hex (e.g., 00AB1234)

Tracked Changes

Insertion:

<w:ins w:id="1" w:author="Claude" w:date="2025-01-01T00:00:00Z">
  <w:r><w:t>inserted text</w:t></w:r>
</w:ins>

Deletion:

<w:del w:id="2" w:author="Claude" w:date="2025-01-01T00:00:00Z">
  <w:r><w:delText>deleted text</w:delText></w:r>
</w:del>

Inside <w:del>: Use <w:delText> instead of <w:t>, and <w:delInstrText> instead of <w:instrText>.

Minimal edits - only mark what changes:

<!-- Change "30 days" to "60 days" -->
<w:r><w:t>The term is </w:t></w:r>
<w:del w:id="1" w:author="Claude" w:date="...">
  <w:r><w:delText>30</w:delText></w:r>
</w:del>
<w:ins w:id="2" w:author="Claude" w:date="...">
  <w:r><w:t>60</w:t></w:r>
</w:ins>
<w:r><w:t> days.</w:t></w:r>

Deleting entire paragraphs/list items - when removing ALL content from a paragraph, also mark the paragraph mark as deleted so it merges with the next paragraph. Add <w:del/> inside <w:pPr><w:rPr>:

<w:p>
  <w:pPr>
    <w:numPr>...</w:numPr>  <!-- list numbering if present -->
    <w:rPr>
      <w:del w:id="1" w:author="Claude" w:date="2025-01-01T00:00:00Z"/>
    </w:rPr>
  </w:pPr>
  <w:del w:id="2" w:author="Claude" w:date="2025-01-01T00:00:00Z">
    <w:r><w:delText>Entire paragraph content being deleted...</w:delText></w:r>
  </w:del>
</w:p>

Without the <w:del/> in <w:pPr><w:rPr>, accepting changes leaves an empty paragraph/list item.

Rejecting another author's insertion - nest deletion inside their insertion:

<w:ins w:author="Jane" w:id="5">
  <w:del w:author="Claude" w:id="10">
    <w:r><w:delText>their inserted text</w:delText></w:r>
  </w:del>
</w:ins>

Restoring another author's deletion - add insertion after (don't modify their deletion):

<w:del w:author="Jane" w:id="5">
  <w:r><w:delText>deleted text</w:delText></w:r>
</w:del>
<w:ins w:author="Claude" w:id="10">
  <w:r><w:t>deleted text</w:t></w:r>
</w:ins>

Comments

After running comment.py (see Step 2), add markers to document.xml. For replies, use --parent flag and nest markers inside the parent's.

CRITICAL: <w:commentRangeStart> and <w:commentRangeEnd> are siblings of <w:r>, never inside <w:r>.

<!-- Comment markers are direct children of w:p, never inside w:r -->
<w:commentRangeStart w:id="0"/>
<w:del w:id="1" w:author="Claude" w:date="2025-01-01T00:00:00Z">
  <w:r><w:delText>deleted</w:delText></w:r>
</w:del>
<w:r><w:t> more text</w:t></w:r>
<w:commentRangeEnd w:id="0"/>
<w:r><w:rPr><w:rStyle w:val="CommentReference"/></w:rPr><w:commentReference w:id="0"/></w:r>

<!-- Comment 0 with reply 1 nested inside -->
<w:commentRangeStart w:id="0"/>
  <w:commentRangeStart w:id="1"/>
  <w:r><w:t>text</w:t></w:r>
  <w:commentRangeEnd w:id="1"/>
<w:commentRangeEnd w:id="0"/>
<w:r><w:rPr><w:rStyle w:val="CommentReference"/></w:rPr><w:commentReference w:id="0"/></w:r>
<w:r><w:rPr><w:rStyle w:val="CommentReference"/></w:rPr><w:commentReference w:id="1"/></w:r>

Images

Add image file to word/media/
Add relationship to word/_rels/document.xml.rels:

<Relationship Id="rId5" Type=".../image" Target="media/image1.png"/>

Add content type to [Content_Types].xml:

<Default Extension="png" ContentType="image/png"/>

Reference in document.xml:

<w:drawing>
  <wp:inline>
    <wp:extent cx="914400" cy="914400"/>  <!-- EMUs: 914400 = 1 inch -->
    <a:graphic>
      <a:graphicData uri=".../picture">
        <pic:pic>
          <pic:blipFill><a:blip r:embed="rId5"/></pic:blipFill>
        </pic:pic>
      </a:graphicData>
    </a:graphic>
  </wp:inline>
</w:drawing>

Dependencies

pandoc: Text extraction
docx: npm install -g docx (new documents)
LibreOffice: PDF conversion (auto-configured for sandboxed environments via scripts/office/soffice.py)
Poppler: pdftoppm for images

About this skill

Automatic

Coding pack

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

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

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IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

LeoYeAI / openclaw-master-skills

skills/docx-cn-1-0-1/SKILL.md

View on GitHub ↗

License MITImported 8/2/2026Version v1Bundled 3 files · scripts

Illustrative Want to see what leoyeai/docx-cn 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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DOCX creation, editing, and analysis

Overview

Quick Reference

Converting .doc to .docx

Reading Content

Converting to Images

Accepting Tracked Changes

Creating New Documents

Setup

Validation

Page Size

Styles (Override Built-in Headings)

Lists (NEVER use unicode bullets)

Tables

Images

Page Breaks

Table of Contents

Headers/Footers

Critical Rules for docx-js

Editing Existing Documents

Step 1: Unpack

Step 2: Edit XML

Step 3: Pack

Common Pitfalls

XML Reference

Schema Compliance

Tracked Changes

Comments

Images

Dependencies

SkillSafety

Source

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