Ready to supercharge your AI agents?

Install any skill in seconds. Free to start, no credit card required.

会议纪要与议题材料（gongwen-minutes） · duyunzhoudyz | DecimalAI

Productivityby duyunzhoudyz

会议纪要与议题材料（gongwen-minutes）

整理会议记录、起草会议纪要、写上会议题材料、列督办清单。只整理不添加，分清同意、原则同意与暂缓，议定事项写明责任单位和时限，议题材料如实写方案并核对“三重一大”前置程序。用户说整理会议纪要、转写稿整理成记录、出个办公会纪要、上会议题材料、督办清单、把会上定的事列个表时使用。会议通知交 gongwen-draft，讲话交 gongwen-speech，新闻稿交 gongwen-brief，三会一课和民主生活会、组织生活会记录交 gongwen-party；装有行业包时，本行业专用文书交对应行业包。不处理音频。

Never made a case worseMaintained

SkillScore

SkillScore86/100

Test results 86

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

32%86%of test cases passed +55 pts

Without skill7 of 22

With skill19 of 22

12 fixed7 passed either way3 still failing0 broke

Measured on gemini-3.8-flash11/3/2026v1

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test task以下是办公室例会讨论实录：副主任李四建议：“办公楼中央空调滤网该换了，建议物业科下周采购一批。” 主任说：“这个事情先放一放，回头看看机关后勤预算盘子再说吧。” 请把上述对话整理成正式会议纪要的议定事项。

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 duyunzhoudyz-gongwen-minutes
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("duyunzhoudyz-gongwen-minutes")
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 duyunzhoudyz-gongwen-minutes

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/duyunzhoudyz-gongwen-minutes/SKILL.md https://app.decimal.ai/s/duyunzhoudyz-gongwen-minutes/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/duyunzhoudyz-gongwen-minutes/SKILL.md

This gets SKILL.md only. The skill's 13 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 duyunzhoudyz-gongwen-minutes

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("duyunzhoudyz-gongwen-minutes")
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/duyunzhoudyz-gongwen-minutes/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from claude_agent_sdk import ClaudeAgentOptions, query

skill = Path(".agents/skills/duyunzhoudyz-gongwen-minutes/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 13 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 duyunzhoudyz-gongwen-minutes

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("duyunzhoudyz-gongwen-minutes")
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/duyunzhoudyz-gongwen-minutes/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/duyunzhoudyz-gongwen-minutes/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 13 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 duyunzhoudyz-gongwen-minutes

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("duyunzhoudyz-gongwen-minutes")
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/duyunzhoudyz-gongwen-minutes/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/duyunzhoudyz-gongwen-minutes/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 13 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 duyunzhoudyz-gongwen-minutes

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("duyunzhoudyz-gongwen-minutes")
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/duyunzhoudyz-gongwen-minutes/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/duyunzhoudyz-gongwen-minutes/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 13 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 duyunzhoudyz-gongwen-minutes

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("duyunzhoudyz-gongwen-minutes")
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/duyunzhoudyz-gongwen-minutes/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/duyunzhoudyz-gongwen-minutes/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 13 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 duyunzhoudyz-gongwen-minutes

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("duyunzhoudyz-gongwen-minutes")
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/duyunzhoudyz-gongwen-minutes/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/duyunzhoudyz-gongwen-minutes/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 13 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 duyunzhoudyz-gongwen-minutes

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("duyunzhoudyz-gongwen-minutes")
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/duyunzhoudyz-gongwen-minutes/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 13 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 duyunzhoudyz-gongwen-minutes

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("duyunzhoudyz-gongwen-minutes")
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/duyunzhoudyz-gongwen-minutes/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/duyunzhoudyz-gongwen-minutes/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 13 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 duyunzhoudyz-gongwen-minutes

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("duyunzhoudyz-gongwen-minutes")
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/duyunzhoudyz-gongwen-minutes/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/duyunzhoudyz-gongwen-minutes/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 13 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 duyunzhoudyz-gongwen-minutes

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("duyunzhoudyz-gongwen-minutes")
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/duyunzhoudyz-gongwen-minutes/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/duyunzhoudyz-gongwen-minutes/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 13 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 duyunzhoudyz-gongwen-minutes

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("duyunzhoudyz-gongwen-minutes")
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/duyunzhoudyz-gongwen-minutes/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/duyunzhoudyz-gongwen-minutes/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 13 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 duyunzhoudyz-gongwen-minutes

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("duyunzhoudyz-gongwen-minutes")
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/duyunzhoudyz-gongwen-minutes/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/duyunzhoudyz-gongwen-minutes/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 13 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 duyunzhoudyz-gongwen-minutes

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/duyunzhoudyz-gongwen-minutes/SKILL.md https://app.decimal.ai/s/duyunzhoudyz-gongwen-minutes/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/duyunzhoudyz-gongwen-minutes/SKILL.md

This gets SKILL.md only. The skill's 13 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/duyunzhoudyz-gongwen-minutes/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/duyunzhoudyz-gongwen-minutes.json

This gets SKILL.md only. The skill's 13 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 11/3/2026
Source: duyunzhoudyz/gongwen-skills ↗
License: NOASSERTION

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

会议纪要与议题材料（gongwen-minutes）

帮办公室、院办、校办、董办的文字工作者写会前的上会议题材料，整理会后的会议记录、纪要和督办清单。先把记录拆成议定事项梳理表，每条结论都找到原话，再成稿。只整理不添加：会上没定的事不写成议定事项，没说的责任单位和时限不补。

适用范围

适用：会议记录（按发言顺序记全过程）；会议纪要（只记议定事项，办公会、专题会、协调会、座谈会、党委〔党组〕会议）；上会议题材料（背景依据、方案比较、需决策事项、前置程序）；督办清单（可转 Excel）。
不适用（转交）：

用户要的	转给
会议通知；根据会议决定起草的请示、函、通知	gongwen-draft
会上的讲话稿、主持词、表态发言	gongwen-speech
把会议写成新闻稿、政务信息	gongwen-brief
“三会一课”记录，民主生活会、组织生活会的会议记录和材料	gongwen-party
把上级文件拆成任务分解表	gongwen-implement
巡视巡察、审计整改台账	gongwen-rectify
纪要成稿后查标点、格式、提法	gongwen-review
排成纪要格式的 Word	gongwen-format
医院党委会、院长办公会议题（装有 gongwen-hospital 时）	gongwen-hospital
国企“三重一大”议题、董事会议案和决议、总经理办公会纪要（装有 gongwen-soe 时）	gongwen-soe
中小学教研活动记录、安全教育记录（装有 gongwen-k12 时）	gongwen-k12

行业包的转交规则：环境中装有上表行业包的（能看到该 skill，或交接卡路线中有它），表中这几类一律转交；党委会与总经理办公会记录在一起的，党委会纪要在本 skill 出，总经理办公会部分在起草说明中写明转交。没装行业包的，按单位画像和 references/units.md 对应小节照常处理，不拒绝。农村“四议两公开”中党员大会审议环节的记录由本 skill 整理。

能调用其他 skill 的环境直接调用；目标 skill 未安装或在网页环境的，按 references/_shared/style/output-format.md 第四部分转交：给交接卡、“新开对话粘贴 dist/prompts/.md 继续”的说明和安装命令。

不处理音频、视频。用户发来录音的，请先转文字再发来，并说明收到后先拆议定事项梳理表、再出纪要或记录（教学模式讲明先后）；涉密或敏感会议的录音不要用联网转写工具。

开工检查

保密（references/_shared/guardrails.md 第一条）：
- 有 Python 时，先运行 python scripts/secret_check.py <文件> 检查保密标识（含页眉页脚），命中即停。
- 出现敏感信号时才在起草说明末尾提示一句，同一会话只说一次；带密级标识或“内部资料”“工作秘密”等标注的，立即停止，不复述、不摘录，告诉用户改用内网模型或删去相关内容后再发。
- 出现身份证号、手机号、病案号、住院号、学号、住址、患者或学生、信访群众的真实姓名的，提醒脱敏；梳理表、记录、纪要一律改用“张某”“138****0000”，起草说明“保密提示”写明。
- 涉及人事任免酝酿、纪律处分、未公开经营数据、投标报价的，不停止，在起草说明末尾提醒一次请用户确认允许在当前模型中处理。人事任免按 references/decisions.md 第五部分：酝酿中的人选评价、考察反映、个人意见不进任何交付物（含一页纸、梳理表、纪要）。
单位画像：先读工作目录 .gongwen/单位画像.md，没有再找 ~/.gongwen/单位画像.md；用户贴在对话开头的按粘贴内容处理。再读 references/_shared/profiles/units/ 下对应单位类型和 references/units.md 对应小节。没有画像按 references/_shared/profiles/roles.md 第九节。
定工作模式：

用户的话	模式
“整理会议记录”“存档”“按发言顺序”“谁说的要对得上”	记录
“出纪要”“发给各科室”“印发”；只说“整理一下会议”、说不清用途的	纪要（起草说明写明记录与纪要的区别）
“上会材料”“议题”“三重一大”“党委会要研究”	议题材料
“督办”“列个表”“跟踪落实”“导成 Excel”	督办清单

纪要和督办清单常一起做；社区两委会议、居民会议按记录做。 4. 定角色模式：按 references/_shared/profiles/roles.md 第一节，本 skill 差异见“角色适配”。党委（党组）会议、传达学习上级精神的议题叠加严谨模式。 5. 查材料，定首轮交付（references/_shared/profiles/roles.md 第十节）：有转写稿、笔记、记录本文字、议程或用户口述的会上内容之一的，任何模式都首轮直接成稿（纪要连同梳理表）。只在以下情形停下，回复开头说明属于哪种：只说开了会、没有任何会上内容的（情形②），只交纪要框架（会议概况和议定事项全部标【待补】）和“请补充的内容”清单，教学模式另用两三句讲清纪要与会议记录的区别；用户明确要先看一页纸或提纲的（情形③）；材料涉密的（情形④，按第1条）。 6. 以下要求不照办，说明原因，其余照常做（references/_shared/guardrails.md 第二条、第六条）：补写一次没有原始记录的会议的纪要或记录；把会上没定的事写进议定事项；倒签会议日期；在议题材料中写“已完成前置程序”却没有依据。教学模式下拒绝时同样讲清纪要与记录的区别。 7. 用户贴了交接卡的，按卡开工，卡上有的不再问（references/_shared/style/output-format.md 第四部分）。

工作流程一　会议纪要

第一步　任务卡

先填任务卡（高效模式只写进起草说明）：会议名称和类型、纪要用途（印发执行或存档）、发送范围、期号、角色模式；看不出的按默认值处理，写进假设，照常成稿。只问影响结构的事，最多 3 个，放回复末尾，按此顺序取舍：纪要还是记录 → 党委会议还是行政会议（记录里看不出时）→ 发送范围。时间、地点、出席名单缺的不问，标【待补】。用户说“直接写”的不问。

第二步　议定事项梳理表

按 references/decisions.md 把记录拆成梳理表，列为序号｜议题｜结论原话（位置）｜结论类型｜责任单位｜完成时限｜状态。

判定“定了没有”（细则见 references/decisions.md 第二部分）：主持人作了结论性表态、记录写明表决结果或“会议同意”的才算定了；个人建议、“再看看”“回头再说”、没有结论的讨论，记“未形成结论”，不进纪要正文和督办清单，列入起草说明“未形成结论的事项”。
结论类型按主持人原话归入同意、原则同意、暂缓、另行研究、退回修改、不同意、听取，不互换（对照表见 decisions.md 第三部分）；当场附带调整的仍是同意，原话有“原则上”“大方向可以”的才是原则同意。
责任单位和时限只写记录中说到的（细则见 decisions.md 第四部分）：责任单位只取主持人原话点名或同段明确指代的，不按汇报单位、主管单位推定，未点名的正文不写，候选单位只放起草说明；“尽快”不改成日期，时限没说的不补，状态记“待补”。
转写存疑的数字、人名，梳理表状态记“待核实”；无单位的大数、带“点”的口语数字（如“一点五亿”）原词照录，不补转写稿没有的计量单位（如“元”）。

第三步　成稿

按 references/minutes-writing.md 写：

结构按会议类型（minutes-writing.md 第一部分）：例会按议题分列，专题会一条主线，协调会写清各方责任边界，座谈会归纳观点。
标题下一行写期号（用户给了的）；导语一段，缺的标【待补】，不写背景意义；导语后另起一行列“出席：×××、×××；列席：×××；请假：×××”名单（minutes-writing.md 第五部分）。会中到达（迟到）的列入出席，括号注”会议进行中到达”，不列为请假或列席；只参与部分议题的列席人员，括号注”仅参与议题×”。记录只写”周四””上周”的，按今天推算为会议日期。
提示语对号入座：认为、指出、强调、要求、议定的内容都要在记录里找得到，没有的不补“会议强调”段。
议定事项一条一事：结论词＋事项＋责任单位＋时限；原则同意写修改要求，暂缓写原因或再议条件。
口语转书面只改说法，不改数字、主体、条件、态度强弱；记录中加引号的做法名称、本单位提法照写。
默认做法：名单列在开头，正文后不再重复，二选一。纪要只写议定事项和必要的会议情况；个人保留意见、不同意见只在会议明确要求记录时写入。记录有冲突、转写存疑的，正文照原词写，列入起草说明。党委会和行政会议的内容分成两份纪要。
会上定的事与法规或上级规定明显冲突的（如决定收取未经批准的费用、要求基层每天报送工作照片），纪要不替会议改结论，照记录写，在起草说明“程序风险提示”中写明依据，建议会议重新研究。

第四步　自检

逐条对账：纪要中每条议定事项都能在梳理表找到“已明确”的结论；正文的数字、日期、文件名都能在记录中找到。有 Python 时运行 python scripts/fact_diff.py 原始记录.txt 正文.txt --ledger，把“正文中有、台账中没有”的数字、日期、书名号逐条改为记录中的说法或删去。
议定事项检查：python scripts/minutes_check.py 正文.txt，报出缺责任单位、缺时限、原则同意未写修改要求、暂缓未写条件、口语残留的条目，记录没说的缺项不补，列入起草说明待补；做了督办清单的加 --list 督办清单.md 对账，牵头与配合颠倒、时限挂错任务都会报出。
机检：python scripts/gongwen_lint.py 正文.txt --doc-type 纪要（记录、议题材料分别用 会议记录、议题材料，引擎只提示不报错）。P0 必改，P1 逐条判断，命中公文白名单的保留（references/_shared/style/ai-tone.md 第二部分）。ELM 要素缺失的，能确定的补写，不能确定的标【待补】；EVD 强评价缺数据的，补用户材料中的数据或改用不带强评价的写法，不得编造数据。
不能运行脚本的，按本文“自检清单”逐项人工检查，起草说明写“未运行机检，已按人工清单检查”。

第五步　交付

能写文件的：在当前目录建 公文/<YYYYMMDD>-<简短标题>/，写入 正文.txt、议定事项梳理表.md；用户粘贴的记录先把身份证号、手机号、病案号和患者、学生、群众的姓名换成代称（其他数字和日期不动），再存为 原始记录.txt 供对账，起草说明保密提示写明保存位置；有督办清单的另写 督办清单.md（和 xlsx）。对话中给出文件位置、议定事项几条和起草说明。
网页环境：按 references/_shared/style/output-format.md 第三部分输出，梳理表、督办清单放在起草说明末尾，标题为“附：议定事项梳理表”“附：督办清单”。还有下一站（如 review、format）的，按第四部分输出更新后的交接卡和新开对话的说明；下一站是行业包、要接着起草另一部分的（如总经理办公会纪要），请用户同时粘贴该部分记录。
起草说明只在对话中给出，不超过 5 行、每行一句：假设、待补（含记录没说的责任单位和时限）、待核实各一行，未形成结论的事项、程序风险提示（仍写依据）、修改说明、保密提示并入其余行；教学模式另附写作要点。回复中不写 skill 名，用描述性说法。

工作流程二　会议记录

按 references/meeting-record.md 整理：

记录头写会议名称、时间、地点、主持人、出席、列席、缺席、记录人、议题，缺时间、地点、出席名单的标【待补】，其余缺项不写，汇总进起草说明。
默认摘要记录：按议程和发言顺序，每人保留观点、理由、条件、数字；用户要“详细”的按 meeting-record.md 第二部分。
发言人对不上的保留原标签，不按内容猜，起草说明待核实一行写明。
不同意见、表决结果如实记录；转写存疑的数字、人名按 meeting-record.md 第五部分原词照录，起草说明待核实一行汇总。
交付 正文-会议记录.txt；同时要纪要的，再按工作流程一出 正文-纪要.txt，共用梳理表。

工作流程三　上会议题材料

按 references/agenda-material.md 写：

一题一议。结构：议题名称、汇报单位、会签部门意见、基本情况和依据、方案比较、需会议决策的事项、前置程序完成情况、附件。
方案比较在正文中用“（一）方案一。……”分项写，不用表格；投入、周期、效果、风险、合规性只写材料里有的，关键项（如投入测算）缺了才标【待补】，不写“材料未提供”。风险高低、是否合规不由本 skill 判断。只有一个方案的不编第二个，起草说明提示补充备选方案。
推荐意见只写汇报单位或用户给出的倾向和理由，不改成两头都说的平衡话；材料没有的，写【待补：汇报单位推荐意见及理由】，不替汇报单位选方案（正误对照见 agenda-material.md 第二部分）。
需决策事项写成能回答“同意或不同意”的句子。
前置程序按单位类型逐项核对（references/agenda-material.md 第三部分，本单位议事规则优先），正文用“1. 公众参与：……”分项写，只写用户提供的完成情况，没说的不写，不写成“已完成”。未经集体决策、前置程序未完成、准备先执行后补程序的，写进起草说明“程序风险提示”（agenda-material.md 第四部分）。对照表作起草说明附表。
篇幅一般 1500～3000 字（工具约定），用户指定字数的按“输出规范”篇幅条；--doc-type 议题材料 机检后交付 正文-议题材料.txt。

工作流程四　督办清单

按 references/supervision-list.md 做：

只从纪要取。列为序号｜议定事项｜纪要位置｜责任单位｜配合单位｜完成时限｜办理状态｜备注。暂缓、不同意、只听取汇报的不进清单；暂缓、另行研究事项下有明确责任单位的准备任务，单列一行，议定事项栏写纪要原话。
责任单位和时限逐字照纪要，没写的该格标【待补】。有 Python 时可运行 python scripts/minutes_check.py 正文.txt --emit-list 督办清单.md 生成草表，再逐行核对。
新建清单状态一律“待办理”；更新进展只改用户提供了进展的行，没有办结依据的不写“已办结”。
转 Excel 按 supervision-list.md 第四部分运行 scripts/md2xlsx.py；不能运行或未生成的，交付 Markdown 表格。

输出规范

纪要、记录、议题材料正文按 references/_shared/style/output-format.md 第一部分：纯文本，层次序数一、（一）1.（1），数字按 GB/T 15835。
正文不出现【待核实】；【待补】只用于必须由用户提供的要素（时间、地点、出席名单、关键方案数据等），全篇一般不超过 3 处；记录没说的责任单位、时限等其余缺项不补不标，汇总进起草说明待补一行。程序风险、未形成结论的事项都写在起草说明里。
梳理表、督办清单、方案比较表、前置程序核对表可用表格，只放在起草说明附表或单独文件中，正文不放表格。
篇幅：用户指定字数的，按 references/_shared/guardrails.md 第四条第2款以±10%为目标；素材撑不起的，纪要、记录只整理不添加，不补会上没有的内容、不为凑字数补段落，起草说明一句话说明差距，可附不超过 3 条补料建议；【待补】不计入字数。

自检清单

角色适配

教学模式：梳理表、纪要和写作要点首轮一次交付；写作要点写纪要的结构安排（当作提纲说明）、纪要与记录的区别、本稿提示语为什么这样用、原则同意与同意的区别（用本稿一处正误对照）。
高效模式：梳理表、纪要、督办清单一次交付；对话只报条数和文件位置；起草说明不展开讲解，程序风险提示每条仍写问题类型和依据条款，一条一行；多次会议可批量整理，每次会议一份纪要。
转译模式：接受零散笔记和口述；只问事实，如“这件事会上谁拍的板”“说没说时限”；梳理表位置写到笔记段落；业务术语照用。
审稿模式分两种。一页纸：领导明确要先过目的（开工检查第5条情形③），先交议定事项每条一句、未形成结论的事项（只写议题和位置）、需要拍板的待确认点（责任不清、时限未说），不写人选评价、考察反映和个人意见，确认后再出正式纪要。纪要对照：拿已写好的纪要和记录来对照的，只列“纪要与记录不一致”清单（位置、纪要原文、记录原话、问题、建议），不重写；标点格式问题建议另行核稿。
严谨模式：党委（党组）会议纪要、传达学习上级精神的议题、对外公开的会议信息，上级精神的名称和表述只用记录和用户提供的原文，缺的照记录原话写，说明请对照原文；附提法核对清单（提法、位置、出处、是否已对照原文）。

参考资料

没有文件系统（网页版、内网提示词版）时，下表中读不到的文件按本文和附录执行，不向用户索要。

文件	何时读取
`references/decisions.md`	纪要第二步：建梳理表、判定结论类型、写责任和时限
`references/minutes-writing.md`	纪要第三步：结构、提示语、议定事项、出席名单
`references/meeting-record.md`	整理会议记录
`references/agenda-material.md`	写议题材料、核对前置程序
`references/supervision-list.md`	做督办清单、更新办理状态、转 Excel
`references/units.md`	读完单位画像后，查本 skill 在该单位类型下的调整
`references/_shared/guardrails.md`、`references/_shared/style/output-format.md`	开工前；与用户要求冲突时；交付和交接卡
`references/_shared/style/ai-tone.md`、`references/_shared/style/defensive.md`	成稿、处理机检结果
`references/_shared/rules/` 下 doc-types.md（7.5）、gbt9704.md（第七部分）、gbt15835.md、jianfu.md	区分纪要与记录；纪要格式和出席列席；数字日期；会议要求有层层加码、留痕时
`references/_shared/profiles/roles.md`、`references/_shared/profiles/units/`	定角色模式、首轮交付、无画像降级；按单位类型读取
`scripts/minutes_check.py`、`fact_diff.py`、`gongwen_lint.py`、`md2xlsx.py`	议定事项检查和督办清单对账；数字日期对账；机检；督办清单转 Excel

About this skill

Automatic

Government & Public Sector pack

SkillSafety

✓ 3 of 3 passed

Code scan14 of 15 checks clean

0 critical · 0 warning · 1 info — scanner v8 — 11/2/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

No issues (informational notes only).

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

duyunzhoudyz / gongwen-skills

skills/gongwen-minutes/SKILL.md

View on GitHub ↗

License PolyForm-Noncommercial-1.0.0Imported 11/2/2026Version v1Bundled 13 files · scripts

Illustrative Want to see what duyunzhoudyz/gongwen-minutes would put in front of your model? Preview the rendered body and check its trigger phrases — no LLM call, no signup.

Related skills

Skills that do similar work, with their headline benchmark lift.

From the same source and nearby in the catalogue.

Ready to supercharge your AI agents?

SkillScore

Safety

What it changes

Track record

Use this skill

会议纪要与议题材料（gongwen-minutes）

适用范围

开工检查

工作流程一 会议纪要

第一步 任务卡

第二步 议定事项梳理表

第三步 成稿

第四步 自检

第五步 交付

工作流程二 会议记录

工作流程三 上会议题材料

工作流程四 督办清单

输出规范

自检清单

角色适配

参考资料

SkillSafety

Source

Related skills

More in the registry

工作流程一　会议纪要

第一步　任务卡

第二步　议定事项梳理表

第三步　成稿

第四步　自检

第五步　交付

工作流程二　会议记录

工作流程三　上会议题材料

工作流程四　督办清单