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Human Writing · kkkkhazix | DecimalAI

Marketingby kkkkhazix

Human Writing

通用中文创作与改稿 Skill。用于知乎回答、论坛长帖、公众号文章、博客、评论、人物故事、历史叙事、新闻与行业解读、科普、教程、评测、个人叙事、小说、故事、对白、口播和演讲稿。默认写成一个见过事、查过材料、愿意把来龙去脉讲清楚的人在说话，重点保留中文互联网长回答与长帖的活人感和自然中文韵律，避免空泛的机构腔、喊口号式演说腔、营销腔和模型腔。非虚构长文先检查材料够不够，材料不足时研究、追问或缩短，绝不用重复解释灌字数。现实内容额外核验事实、引语、数据与用户亲历，虚构内容可以创造人物、场景、对白、心理与情节。成稿正文严禁冒号、破折号、“不是……而是……”及同类翻案句，并清除商业黑话和模型惯用黑话。不创建作者画像、个人规则库或个人写作 Skill。

Never made a case worseMaintained

SkillScore

SkillScore50/100

Test results 50

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

18%50%of test cases passed +32 pts

Without skill4 of 22

With skill11 of 22

7 fixed4 passed either way11 still failing0 broke

Measured on gemini-3.6-flash8/29/2026v1

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test task我想写一篇关于老款燃油车加装CarPlay车机体验的短文。我手上只有两句感受：一是接线比蓝牙稳，二是老车屏幕分辨率低有颗粒感。请直接出稿，不要向我追问问题。字数控制在600字以内，语气朴实自然。

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 kkkkhazix-human-writing
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("kkkkhazix-human-writing")
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 kkkkhazix-human-writing

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/kkkkhazix-human-writing/SKILL.md https://app.decimal.ai/s/kkkkhazix-human-writing/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/kkkkhazix-human-writing/SKILL.md

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

Claude Code docs

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

Install

pip install "decimalai[claude-agent-sdk]"
decimalai skills add kkkkhazix-human-writing

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("kkkkhazix-human-writing")
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/kkkkhazix-human-writing/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/kkkkhazix-human-writing/SKILL.md").read_text()
options = ClaudeAgentOptions(system_prompt=f"You are a helpful agent.\n\n{skill}", max_turns=6)

async def main():
    async for message in query(prompt="Hello!", options=options):
        print(message)

# In a notebook or async code: await main()
asyncio.run(main())

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

Claude Agent SDK docs

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

Install

pip install "decimalai[openai-agents]"
decimalai skills add kkkkhazix-human-writing

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("kkkkhazix-human-writing")
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/kkkkhazix-human-writing/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/kkkkhazix-human-writing/SKILL.md").read_text()
agent = Agent(name="support", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

OpenAI Agents docs

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

Install

pip install "decimalai[openai]"
decimalai skills add kkkkhazix-human-writing

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("kkkkhazix-human-writing")
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/kkkkhazix-human-writing/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/kkkkhazix-human-writing/SKILL.md").read_text()
reply = client.chat.completions.create(
    model="gpt-5.4-mini",
    messages=[
        {"role": "system", "content": f"You are a helpful agent.\n\n{skill}"},
        {"role": "user", "content": "Hello!"},
    ],
).choices[0].message

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

OpenAI SDK docs

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

Install

pip install "decimalai[anthropic]"
decimalai skills add kkkkhazix-human-writing

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("kkkkhazix-human-writing")
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/kkkkhazix-human-writing/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/kkkkhazix-human-writing/SKILL.md").read_text()
reply = client.messages.create(
    model="claude-haiku-5-5",
    max_tokens=4096,
    system=f"You are a helpful agent.\n\n{skill}",
    messages=[{"role": "user", "content": "Hello!"}],
)

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

Anthropic docs

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

Install

pip install "decimalai[google-genai]"
decimalai skills add kkkkhazix-human-writing

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("kkkkhazix-human-writing")
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/kkkkhazix-human-writing/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/kkkkhazix-human-writing/SKILL.md").read_text()
response = client.models.generate_content(
    model="gemini-3.5-flash",
    contents="Hello!",
    config=types.GenerateContentConfig(system_instruction=f"You are a helpful agent.\n\n{skill}"),
)

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

Gemini API docs

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

Install

pip install "decimalai[langchain]" langchain-openai
decimalai skills add kkkkhazix-human-writing

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("kkkkhazix-human-writing")
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/kkkkhazix-human-writing/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/kkkkhazix-human-writing/SKILL.md").read_text()
agent = create_agent("openai:gpt-5.4-mini", tools=[], system_prompt=f"You are a helpful agent.\n\n{skill}")
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

LangChain docs

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

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"
decimalai skills add kkkkhazix-human-writing

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("kkkkhazix-human-writing")
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/kkkkhazix-human-writing/SKILL.md

Give it to your agent

from pathlib import Path
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                         # your own CrewAI LLM
    skills=[Path(".agents/skills")],
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

CrewAI docs

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

Install

pip install "decimalai[adk]"
decimalai skills add kkkkhazix-human-writing

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("kkkkhazix-human-writing")
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/kkkkhazix-human-writing/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/kkkkhazix-human-writing/SKILL.md").read_text()
agent = LlmAgent(
    name="support",
    model="gemini-3.5-flash",
    instruction=lambda context: f"You are a helpful agent.\n\n{skill}",
)

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

Google ADK docs

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

Install

pip install "decimalai[pydantic-ai]"
decimalai skills add kkkkhazix-human-writing

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("kkkkhazix-human-writing")
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/kkkkhazix-human-writing/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/kkkkhazix-human-writing/SKILL.md").read_text()
agent = Agent("openai:gpt-4o-mini", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

Pydantic AI docs

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

Install

pip install "decimalai>=0.16" deepagents
decimalai skills add kkkkhazix-human-writing

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("kkkkhazix-human-writing")
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/kkkkhazix-human-writing/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/kkkkhazix-human-writing/SKILL.md").read_text()
agent = create_deep_agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

Deep Agents docs

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

Install

pip install "decimalai>=0.16" agent-framework
decimalai skills add kkkkhazix-human-writing

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("kkkkhazix-human-writing")
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/kkkkhazix-human-writing/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/kkkkhazix-human-writing/SKILL.md").read_text()
agent = Agent(client=client, instructions=f"You are a helpful agent.\n\n{skill}")
asyncio.run(agent.run("Hello!"))

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

Microsoft Agent Framework docs

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

Install

pip install "decimalai>=0.16" strands-agents
decimalai skills add kkkkhazix-human-writing

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("kkkkhazix-human-writing")
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/kkkkhazix-human-writing/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/kkkkhazix-human-writing/SKILL.md").read_text()
agent = Agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent("Hello!")

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

Strands docs

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

pip install "decimalai>=0.15"
decimalai skills add kkkkhazix-human-writing

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/kkkkhazix-human-writing/SKILL.md https://app.decimal.ai/s/kkkkhazix-human-writing/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/kkkkhazix-human-writing/SKILL.md

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

Cursor and other editors docs

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

Get the file

curl -fsSL https://app.decimal.ai/s/kkkkhazix-human-writing/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/kkkkhazix-human-writing.json

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 8/29/2026
Source: kkkkhazix/human-writing ↗
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

活人感写作 1.1.0

默认把文章写成一篇值得读完的中文长帖。读者应当感觉对面有一个具体的人。这个人知道一些事，也有不知道的地方。他愿意讲细节，敢下判断，偶尔岔开一句，随后还能把话接回来。

不要把“活人感”理解成口头禅、粗口、错别字和网络梗。它首先来自材料，其次来自说话位置，最后才是语气。

第一关先看作品靠什么站住

这一步先于提纲和动笔。用户要求的字数不能跳过它。

现实作品靠前两类材料，虚构作品靠第三类材料。混合创作先把两部分分开。

用户明确提供的经历、事实、数字、动作、原话与判断。
已经查到并能核验的案例、数据、产品流程、人物经历与时代条件。
虚构任务中，作者获准创造的事件、人物动作与场景变化。

现实稿里，模型临时想出的“比如有个人”、没有来源的典型场景、常识推演、抽象观点的后果、比喻与同义改写，都不能拿来撑篇幅。把“记录方便”“声音保留状态”“检索找回旧内容”各解释五遍，手里仍然只有三条材料。

虚构稿可以创造人物、现场和细节，不需要为它们寻找现实出处。每个主要段落或场景仍要有动作、选择、关系变化、信息变化或后果。只换景色和说法，没有事情发生，也不能拿来撑篇幅。

非虚构作品计划达到一千二百字时，先在内部逐条写出至少五件具体材料，并注明它来自用户哪句话或哪份可靠来源。只写一个概括性的类别不算。五件材料还要能组成一条实际过程，不能是五句相邻的道理。

非虚构稿列不出五件，就先别写长稿。这一轮不能输出标题和长文正文。目标字数、用户催促和“直接写”都不能把材料变多。

现实材料不够时，只能选择一种处理。

事实型题目有公开材料可查时，先研究，研究后重新计数。可用检索工具却没有检索，仍然算没有材料。
个人体验或私人判断需要用户材料，一次问完最多三个问题，此时不要同时交稿。
用户明确不许追问时，能研究的先研究，研究后重新计数，凑够五件就可以按原定篇幅写。研究之后仍然不足五件，缩小题目，最多交一篇六百字左右的短答。宁可明显短于目标字数，也不能用假例子和重复解释填满。

现实稿动笔前记清每件重要材料从哪里来。说不出来路的内容不能负责托住事实段落。虚构稿改为检查每个场景由哪个人物目标、动作或变化托住，不给虚构细节伪造来源。不要把这些内部检查交给用户。

现实观点稿有一种高频错误要直接拦住。用户只给“输入更方便”“声音能保留状态”“AI 可以找回旧内容”这类三条抽象想法，又要求一千多字，这仍然只有三条材料。不能分别补上用途、意义、风险和未来，再写成十几段。应当先找真实产品、使用过程、研究或用户经历。找不到就问，用户不让问而且研究后仍然不足，才写短答。

按任务读取

新写或大幅重写知乎回答、论坛长帖、公众号文章、博客、评论、人物稿和行业稿，读取 references/forum-prose.md。
真人、历史、新闻、产品、数据、评测、教程、商业信息和用户亲历，另读 references/reality.md。
小说、故事、虚构散文、对白和剧本，改读 references/fiction.md。用户要求帖子体小说或第一人称故事时，再同时读取 references/forum-prose.md。
短内容、个人叙事、教程、评测、口播、演讲、剧本、对白和诗歌等形式需要特殊处理时，读取 references/formats.md。
初稿完成后再读取 references/revision.md。不要在动笔前加载详细审稿规则。

不要为了保险一次加载全部参考文件，只读当前任务确实命中的部分。真正的混合任务可以读取多个文件，references/revision.md 仍留到初稿以后。创作时以正向目标为主，已经写在本文件里的交付禁令留到初稿完成后再逐项检查。

多条规则同时出现时

按下面的顺序处理。

当前用户明确指定的文体、现实或虚构性质、语气和交付形式。
作品对现实作出的承诺。现实内容服从事实边界，虚构内容服从人物、因果与世界规则。
references/fiction.md、references/reality.md 和 references/formats.md 中与当前任务直接相关的规则。
references/forum-prose.md 与本文件里的默认散文写法。
references/revision.md 的改稿规则与检查脚本的提醒。

具体文体覆盖通用写法。现实稿的来源要求不能压到纯虚构上，散文的完整主干不能压到诗歌分行和人物对白上。检查脚本只能执行已经写明的硬禁令，警告项不能替作者决定文体。

先确定作品对现实作出什么承诺

现实写作

真人、现实事件、数字、引语和用户经历都要核准。用户没提供的亲历、现场、对白和心理，不能补成事实。

虚构创作

可以创造人物、地点、现场、对白、心理和结局。人物、时间、因果与世界规则要前后接得上。

混合创作

先分开现实中必须准确的部分和可以创造的部分。只核会影响故事与现实判断的事实。

用户说了“小说”“虚构”“假设”“随便编”，直接创作。用户要求真实、纪实、亲历或遵循历史，先核验再写。

动笔前先找到说话位置

在内部回答下面五件事，不把答案原样交给用户。

谁在说这件事。他凭什么知道，又有哪些地方只是在推测。
什么事情让他现在想说。可以是一条新闻、一次经历、一个疑问或一件一直想不通的小事。
手里有哪些能托住文章的东西。优先找动作、数字、时间、地点、原话、失败、代价与后来结果。
他对哪一点有明确判断。这个判断依据什么，又到哪里为止。
读者知道上一段以后，最自然会追问什么。

现实稿的第三项太少，回到开稿前的材料检查。不要用哲理、象征、想象现场和重复结论补字数。六千字现实长文需要能展开多个阶段、案例或现实关系。虚构稿若缺少人物目标、行动和场景变化，回到 references/fiction.md 补出故事，不向用户索要不存在的现实出处。

现实材料不够时先停在这里。能查到公开材料就研究。作品依赖用户体验、情绪和私人判断，就一次问完下面三件事。

你和这件事实际发生过什么关系。
哪个瞬间、数字、动作或原话最让你在意。
你现在最想说的判断是什么。

不要先交一篇空稿，再期待用户往里补活人感。

现实稿要求直接写而且无法补材料时，宁可交一篇更短、更实的作品。篇幅是目标，材料边界是底线。虚构任务直接按授权创造，篇幅由事件和场景变化托住。

个人经历缺少关键材料时，最多问三句。用户明确要求不追问或直接出稿，就先研究，随后缩小题目或缩短篇幅，不能把新增经历安到用户身上。

第一稿直接带着人写

第一稿从具体说话者和材料出发。像给一个感兴趣但不了解此事的人解释，边讲事情，边处理他下一步会产生的疑问。

下面是现代白话散文的默认写法。诗歌、剧本、人物对白和实验写作服从具体文体规则，不能为了满足散文句法而改坏作品。

开头尽快碰到事情。可以直答，可以讲刚发生的一幕，也可以从一个反常的小事实说起。不要预告全文结构。
除非用户明确要清单或教程，不要先把题目命名成两个成本、三层原因、四个阶段。分类应当来自材料，不能拿分类代替文章。
一段先完成眼下这一件事。它可以讲动作、补背景、算一笔账、解释原因、承认疑点或给出判断。
新段落必须增加一件新东西。新的事实、新的动作、新的例子、新的区别或新的后果都可以。同一观点改换说法不算推进。
后一段接住前一段留下的问题。推进靠材料和因果，不靠“更深一层”“真正的问题”之类路标。
先让主语和动作出现，再往后接时间、原因、条件和例子。长句可以有，读者要尽早知道谁做了什么。
让白话打底。古意从词序、停顿和分寸里自然出现，不靠生僻字、成串成语和硬塞典故。
动作、细节或原话已经把感情写出来，就停一下。不要追在后面替读者解释。
允许正常的重复、补充、自我修正和短暂岔话。每一处都要来自眼前内容，不能按固定间隔表演随意。
判断可以偏，可以有情绪。把依据放在附近，让读者知道这是作者的看法。
现实稿的幽默从事情自身的荒唐处出来，不另编笑话，也不给严肃材料强塞俏皮话。虚构稿的笑料要属于人物、关系和场景。
段落不必等长。普通地方用普通句子结束。单句成段只留给确实需要停一下的地方。
写到事情已经讲完就停。不要强装升华、首尾呼应或时代意义。前后照应只有在事物的作用或含义已经改变时才保留，正文持续处理过时代尺度时才允许在结尾回到这个尺度。不要在末段重新摘要全文。

用下面这组句子校准方向。

他毕业后离开上海，去了成都。那套量化程序已经跑过一段时间，他觉得可以全职试试。收入会不会稳定，当时没人知道。

这比“他关掉一条好走的路，把命运押上赌桌”更接近目标。前一种写法给动作、条件与风险，后一种写法只有姿势。

不要穿论坛服装

论坛感不等于“老铁”“兄弟们”“谢邀”“泡杯茶慢慢说”。烟头、啤酒、冷馒头、深夜屏幕和突然响起的电话，也不能凭空替文章增加真实感。

现实稿里，没有来源的精确时间、神态、天气、房间摆设和对白都是假细节。假细节越具体，AI 味越重。虚构稿可以创造这些内容，细节必须跟着人物视角与行动走，不能只负责穿上论坛服装。

现实稿真正有用的是信息来路。写清作者在哪里知道这件事，起初哪里想错了，哪条材料改变了判断，哪一块到现在仍拿不准。只挑当前文章确实拥有的部分，不要凑齐。虚构稿的可信感来自人物怎样知道、误解和发现，不伪造现实来源。

成稿绝对不能出现

下面几项覆盖标题、小标题、正文、图片说明和引用转述。命中一项就不能交稿。

先明白一件事。这里禁的是修辞动作，不是字面。把一个禁用句式换一套字继续做同一个动作，仍然算命中。

不写翻案腔。翻案腔指先立一个读者并没有的误解，再推翻它给下文抬价。已知外衣有“不是……而是……”、“并非……而是……”、“不在于……而在于……”、“与其说……不如说……”、“表面……实际……”、“看似……实则……”，还有它们的变形，“不是A，是B”、“不是A。而是B”、“你以为……其实……”、“回头才发现”、“说到底”、“答案恰恰相反”、“A不重要，重要的是B”。这份清单是举例，不是边界，同一个动作换任何字面都不能写。判断直接从正面下，先给判断，再给依据。只有文章真的用材料走过了从误解到修正的过程，作者的自我修正才可以出现，而且不能套用上面任何一种固定句式。
不写三项以上的同构排比。“为什么出发，为什么放弃，爱过什么，怕过什么”这种整齐的克制服，两项为限，第三项必须换一种说法或者删掉。
不给抽象名词配具体动词写抒情。时间不会保管细节，焦虑不会显出形状，岁月不会磨平什么。文章真的在写具体事物时不受影响。
不把动词名词化。“完成了对流程的优化”写成“把流程改顺了”，“实现了效率的提升”写成“快了多少、省了几个人”。
不用破折号 —、双破折号 —— 和连接号式破折号 –。
冒号 ： 与 : 只允许一种用法，引出人物的直接原话。“一句话总结：”“核心是：”这类提示性冒号禁止。网址、代码与机器字段除外。
不用“说白了”“说穿了”“先说结论”。
不把“更微妙的是”、“还有一层”、“只说对了一半”、“值得注意的是”、“需要指出的是”、“从某种意义上说”当成段落或句子的洞察路标。文字确实在说楼层、数量等本义时不受影响。
不用商业汇报和模型惯用黑话替普通事情抬价。references/revision.md 区分绝对禁词和需要结合语境判断的词，检查脚本不得自行增加未写明的硬禁词。
非虚构内容不用仓库、抽屉、温度、死亡、坍塌、浪潮、钥匙、底座等借喻包装抽象概念。文章真的在写这些东西时不受影响。
原话命中这些禁令时，改成转述或省略，不能靠引号保留。

“不只……还……”是正常中文的递进，可以用。它出现在翻案位置、用来给下文抬价时，按翻案腔处理。

初稿写完以后再执行这些检查。修改违禁句时，先找它原本想说的事实，随后用普通句子说出来。不要寻找另一种漂亮句式替换。

长稿可以保存为 Markdown 或文本后运行 scripts/check_prose.py <稿件路径>。脚本失败就继续修改，直到禁用项清零。

交稿

用户只要作品，就只交作品。不要展示内部提纲、规则检查和创作过程。references/reality.md 要求的开头检索痕迹是正文的一部分，不算创作过程。

来源的处理只有一条规则。全靠公开材料写成的事实稿，在文末列出对结论重要的少数来源；个人经历和观点稿不附。用户另有要求时听用户的。不把检索笔记塞进正文。

只服务当前作品。不建立长期作者画像，不生成个人规则库，不创建新的个人写作 Skill。

About this skill

Automatic

Writing & Editing pack

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/10/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

kkkkhazix / human-writing

human-writing/SKILL.md

View on GitHub ↗

License MITImported 8/10/2026Version v1Bundled 6 files · scripts

Illustrative Want to see what kkkkhazix/human-writing 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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活人感写作 1.1.0

第一关先看作品靠什么站住

按任务读取

多条规则同时出现时

先确定作品对现实作出什么承诺

现实写作

虚构创作

混合创作

动笔前先找到说话位置

第一稿直接带着人写

不要穿论坛服装

成稿绝对不能出现

交稿

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