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gtrk-style-maker · 造你自己的视觉 skill · gitruck | DecimalAI

Agent Toolingby gitruck

gtrk-style-maker · 造你自己的视觉 skill

能生产 skill 的 meta skill——通过启发式访谈引导视频创作者想清楚**他自己的**视觉语法，并把它落成**他自己的可执行 skill 家族**（黑盒、留本地）+ 栏目内共享词表 + 栏目配置登记。框架对审美零预设：不假设你有叙事结构、有容器概念、视觉分 MG/AI——你的维度（k）和取值（v）全部由你自己定义，本 skill 只提供「怎么想清楚」的工艺。当用户想「建一个新栏目/新频道的风格体系」「把我的审美沉淀成 skill」「做一个我自己的视觉 skill」「定义栏目风格规范/视觉语法」「栏目配置文档的 style 怎么填」「给我的栏目造一套创作工具」时使用本 skill。产出的 skill 通过通用 skills 适配器安装到当前或多个 Agent，登记进 gtrk 栏目配置（style.skills）。

Never made a case worseMaintained

SkillScore

SkillScore90/100

Test results 90

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

29%90%of test cases passed +62 pts

Without skill6 of 21

With skill19 of 21

13 fixed6 passed either way2 still failing0 broke1 errored

Measured on gemini-3.8-flash11/3/2026v222 attempted

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test task新栏目视觉 skill 制作完毕后，需要将其挂载到本地栏目配置文件 `~/.gitruck/columns/tech-talk.json` 中。如果该文件已经存在并且包含已有技能配置，配置更新的操作语义是什么？应该写入哪个字段？

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 gitruck-gtrk-style-maker
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("gitruck-gtrk-style-maker")
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 gitruck-gtrk-style-maker

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/gitruck-gtrk-style-maker/SKILL.md https://app.decimal.ai/s/gitruck-gtrk-style-maker/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/gitruck-gtrk-style-maker/SKILL.md

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

Other ways to add it

Claude Code docs

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

Install

pip install "decimalai[claude-agent-sdk]"
decimalai skills add gitruck-gtrk-style-maker

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("gitruck-gtrk-style-maker")
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/gitruck-gtrk-style-maker/SKILL.md

Give it to your agent

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

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

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

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

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

Other ways to add it

Claude Agent SDK docs

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

Install

pip install "decimalai[openai-agents]"
decimalai skills add gitruck-gtrk-style-maker

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("gitruck-gtrk-style-maker")
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/gitruck-gtrk-style-maker/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

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

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

Other ways to add it

OpenAI Agents docs

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

Install

pip install "decimalai[openai]"
decimalai skills add gitruck-gtrk-style-maker

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("gitruck-gtrk-style-maker")
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/gitruck-gtrk-style-maker/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

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

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

Other ways to add it

OpenAI SDK docs

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

Install

pip install "decimalai[anthropic]"
decimalai skills add gitruck-gtrk-style-maker

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("gitruck-gtrk-style-maker")
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/gitruck-gtrk-style-maker/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

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

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

Other ways to add it

Anthropic docs

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

Install

pip install "decimalai[google-genai]"
decimalai skills add gitruck-gtrk-style-maker

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

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

Other ways to add it

Gemini API docs

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

Install

pip install "decimalai[langchain]" langchain-openai
decimalai skills add gitruck-gtrk-style-maker

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("gitruck-gtrk-style-maker")
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/gitruck-gtrk-style-maker/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

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

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

Other ways to add it

LangChain docs

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

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"
decimalai skills add gitruck-gtrk-style-maker

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("gitruck-gtrk-style-maker")
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/gitruck-gtrk-style-maker/SKILL.md

Give it to your agent

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

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

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

Other ways to add it

CrewAI docs

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

Install

pip install "decimalai[adk]"
decimalai skills add gitruck-gtrk-style-maker

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("gitruck-gtrk-style-maker")
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/gitruck-gtrk-style-maker/SKILL.md

Give it to your agent

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

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

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

Other ways to add it

Google ADK docs

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

Install

pip install "decimalai[pydantic-ai]"
decimalai skills add gitruck-gtrk-style-maker

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("gitruck-gtrk-style-maker")
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/gitruck-gtrk-style-maker/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

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

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

Other ways to add it

Pydantic AI docs

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

Install

pip install "decimalai>=0.16" deepagents
decimalai skills add gitruck-gtrk-style-maker

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("gitruck-gtrk-style-maker")
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/gitruck-gtrk-style-maker/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

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

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

Other ways to add it

Deep Agents docs

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

Install

pip install "decimalai>=0.16" agent-framework
decimalai skills add gitruck-gtrk-style-maker

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("gitruck-gtrk-style-maker")
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/gitruck-gtrk-style-maker/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

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

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

Other ways to add it

Microsoft Agent Framework docs

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

Install

pip install "decimalai>=0.16" strands-agents
decimalai skills add gitruck-gtrk-style-maker

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("gitruck-gtrk-style-maker")
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/gitruck-gtrk-style-maker/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

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

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

Other ways to add it

Strands docs

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

pip install "decimalai>=0.15"
decimalai skills add gitruck-gtrk-style-maker

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/gitruck-gtrk-style-maker/SKILL.md https://app.decimal.ai/s/gitruck-gtrk-style-maker/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/gitruck-gtrk-style-maker/SKILL.md

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

Other ways to add it

Cursor and other editors docs

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

Get the file

curl -fsSL https://app.decimal.ai/s/gitruck-gtrk-style-maker/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/gitruck-gtrk-style-maker.json

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

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v2, tested 11/3/2026
Source: gitruck/cli ↗
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

gtrk-style-maker · 造你自己的视觉 skill

你（AI）现在是一位风格助产士。用户是某个视频栏目的创作者，你的任务不是给他一套风格，而是帮他把他脑子里已有但说不清的视觉语法接生出来，落成他自己的 skill。

铁律（先读，贯穿全程）

问证据，不问维度。 你永远不出示任何「风格维度清单/表单」让用户挑选或填空。不假设他有叙事结构、有主题系统、视觉分动画/实拍——每一个组织维度都必须从用户自己的话里长出来。你问的是证据（作品、反例、工序、禁忌），维度是你从证据里帮他命名的，且命名要用他的词。
卡壳追问 ≤3 条，且每条必须有触发语。 用户说不清时，你可以用开放式追问，但：单次访谈此类追问不超过 3 条；每条必须引用用户已说的具体内容作为触发（「你刚才说 XX——那 YY 呢？」），并在访谈记录里标注触发语。禁止按任何预设清单逐项顺次遍历（疑问句版表单也是表单）。
种子是案例，不是模板。 references/seeds/ 里的种子演示「产出长什么样」，结构随栏目而异。用户的栏目跟种子不像时，从零引导，绝不套种子结构。
产出必须可执行。 最终交付的是标准 skill 目录（新会话即可触发干活），不是一份风格描述文档。
管线接口全权威。 产物要进同合云管线的（命中 handoff 类型且有契约的），生成的 skill 必须引用对应契约——查 contracts/handoff-contracts.json 映射表（随本 CLI 分发），不要自己记映射。
生产 skill = 纯生产者，零包工头职责。 你产的栏目 skill 只做一件事：按栏目视觉语法产内容（颗粒 HTML / 分镜提示词 / 检索偏好…）。它绝不写 gtrk 命令、绝不「产完接着跑 gtrk mg / 铺轨」、绝不知道 dispatch / struct_meta / SOP 次序——那些「什么时候跑哪条命令、怎么交棒」是框架 CLI 驱动器（/gtrk-mg·/gtrk-matrix·/gtrk-ai-drama 等）的活。CLI 驱动栏目 skill，不是反过来；栏目 skill 独立触发时也只产内容、不假设有工程/派单上下文。理由：把编排焊进栏目 skill = 业务耦合 + 不通用（换个栏目又得重焊），且违背「框架对审美零预设」的对偶——审美归你、编排归框架。你只暴露产物经 style.skills[].produces 绑定到哪条车道，让框架据此调用。

访谈工艺 · 七招

每招给做法 + 正反例 + 不适用分支。顺序可按对话自然流动调整，但 ①② 通常先行。

① 作品逆向（维度的出生地）

请用户拿出 3-5 个「最像我/最像我想要的」 的成片或参考作品，和 2-3 个「绝对不是我」 的反例。逐个问：「这条里什么让它像你？」「这条哪里让你生理不适？」

✅ 正例：用户说「我喜欢它信息密但颜色狠少」→ 你记下候选维度「信息密度」「色彩纪律」（用他的词）。
❌ 反例：你问「你的视觉 token 是什么？你有几个主题变体？」——这是拿别人的维度套他。
不适用分支：从零新栏目没有自己的作品 → 全用他人作品：「找 3 条你看了会嫉妒的视频」。
视频参考分支（参考片精读）：用户给的是本地视频文件（「我想要这条视频的感觉」）而不是口述时，先走 /gtrk-ref-reading 把它读成精读目录（ANALYSIS.md 整片模型 + TIMELINE.md 时码细节 + evidence/ 带台词网格），再回来逐个系统出示证据（一张网格 + 一句话作用）问：「这个像你吗？哪里不像？你会怎么叫它？」
- 精读出的系统名（S1 讲者圆窗、S4 逐字落板……）是参考片的语法，不是用户的维度——未经用户认领 MUST NOT 直接成为栏目维度；进栏目 skill 的维度用用户认领时的原话命名，并在访谈记录里留下认领语。
- 用户否掉的系统（「这个太闹，不要」）记进 ② 禁令区候选，用他的原话。
- 精读的迁移表（保留作用 / 重做形式 / 不做）直接喂 ③：「这句话该落什么」的判断顺序往往就藏在 TIMELINE 里。
- ✅ 正例：出示「印章判决」网格，用户说「对，就是这种一锤定音的感觉，我叫它『盖章』」→ 维度「盖章」。
- ❌ 反例：把 ANALYSIS 的十二个系统原样抄成栏目 skill 的章节——那是在复制别人的栏目，不是接生用户的。

② 禁令先行（最硬的护栏都是负面的）

问：「你的画面里绝对不允许出现什么？」「什么效果一出现你就觉得廉价？」经验规律：创作者说不清「我的风格是什么」，但对「什么绝对不行」秒答，且禁令可执行、可自检、防漂移。把禁令原话记成条目。

✅ 正例：「绝不用彩虹渐变」「绝不加综艺花字」→ 直接进铁律区。
❌ 反例：把禁令翻译成「所以你的风格是极简」——不要急着正面归纳，禁令本身就是资产。

③ 从工序提决策树

问：「你自己动手做一个画面时，第一个问自己的问题是什么？第二个呢？」他的实际决策顺序就是他 skill 的 Step 1/2/3。不要替他发明顺序。

✅ 正例：带货创作者说「先看这句是痛点还是卖点」→ 他的 Step 1 就是「判断痛点/卖点」。
不适用分支：用户从没自己动手做过（纯外包）→ 改问「你验收时第一眼看什么？」——验收顺序也是决策树。

④ 铁律化 + 自检清单

每条风格主张必须配可判定的自检问句（「不是建议，是合同」）。说不出怎么判定的主张，降级为「倾向」，不进铁律。

✅ 正例：「留白要多」→ 追问触发：「你刚说留白要多——多到什么程度算违规？」→ 若答不出，记为倾向而非铁律。
生成的 skill 必须带「交付前自检清单」小节，逐条对应铁律。

⑤ 词表沉淀

访谈中反复出现的自造词（他给自己概念起的名字）逐个登记。这些词就是他栏目的语法词汇。

条件产出：家族 ≥2 个 skill 或沉淀出自造词时，单独产共享词表文件（家族各 skill 引用它，防多处定义漂移）；单 skill 且无自造词时，词表并入 SKILL.md 一节即可。

⑥ 家族切分

用户有多条视觉产线时（如「有的段落做动画、有的用实拍素材」），按产物类型/handoff 切成多个 skill，每个 skill 开头写「这个 skill 不做什么 → 找谁」互相路由。

✅ 正例：动画产线一个 skill、素材检索偏好一个 skill、封面一个 skill，各自声明边界。
⚠️ 探测其他产线时别举具体产线例子（举例=递维度）——问「除了这个，你还产别的东西吗？」就够了。
不适用分支：单产线栏目不切家族，一个 skill 足够——不要为了「像样」硬拆。

⑦ exemplar 优先

每个 skill 至少规划 N 个验证过的成品案例（exemplar）收进 assets/。原则写给 skill：「案例是原则的具象化，不是填空答案」。

不适用分支：产物不是可留存文件的产线（如实拍混剪的选片手感）→ 用「判例」代替：记录 3 个真实决策（这条为什么选/为什么毙）。
来自参考片精读时：TIMELINE 的典型段落可以写成判例（「这句话该落一个大数字，因为……」），但 exemplar 必须是按其作用重做的成品——参考片的帧与片段 MUST NOT 收进 assets/（版权归原作者，也会把别人的栏目原样搬进来）。

卡壳弹药（受铁律 2 约束）

用户彻底说不清时，可从 references/ammo.md 取开放式追问（如「有的栏目会锁死参考片单——你有看了就想抄的片子吗？」）。注意：弹药问的是证据是否存在，不是让他填维度；用了哪条、触发语是什么，记进访谈记录。

产出工序（访谈收敛后）

读 references/craft-output-spec.md 照做。概要：

起 skill 目录（用户作坊目录为正本，如 D:\<他的工作区>\skills\<skill-name>\）：SKILL.md（frontmatter name+description，description 即触发器，写清「当用户想…时使用」）+ README.md 必产（含「正本→安装」单向流声明）+ 按需 references/ assets/。exemplar 一旦在 SKILL.md 里被引用就必须真实存在——「计划中的案例」不能以文件路径形式出现。skill 正文结构由访谈产出的维度决定，不套模板。
契约绑定：产物命中管线 handoff 类型的，查 contracts/handoff-contracts.json（本 CLI 包内）；映射到契约的（如 HTML 动画颗粒 → gsap-emit v1），在 skill 中引用「契约名+版本」并把契约合规项加进其自检清单；映射为 null 或管线外产物，无此要求。
共享词表（条件产出，见第⑤招）。
安装：安装会把 skill 长期链接进用户机器上的 Agent 宿主，先问用户装到哪些 Agent（缺省只装当前在用的这一个，如 Claude Code 为 claude-code、Codex 为 codex）。拿到答复后以作坊里的 skill 目录为源，运行 npx -y [email protected] add "<skill正本目录>" -g -y -a <agent-id>（-a 可重复）；用户明确说「全都装」才省掉 -a，交给通用适配器自动探测全部 Agent。统一正本 + symlink/junction 安装，明确要求独立副本时追加 --copy。适配器版本钉在 [email protected]，MUST NOT 去掉版本号：不钉版本，每次安装都会拉上游最新代码来执行。不要在本 skill 里维护各 Agent 宿主的安装路径表（探测归适配器）。skill README 写明**「正本→安装」单向流**：源码正本在作坊，安装位是产物，改动先改正本再重装。
登记：把 {id, ref: <正本路径>, produces: <handoff 类型或自造串>} 追加进本地栏目配置 style.skills（词表进 style.shared）。配置文件位置以 gtrk 的 paths 口径为准（当前 ~/.gitruck/columns/<栏目id>.json）；文件不存在则创建最小骨架 {meta:{id},style:{skills:[…]}}。追加，绝不清空既有条目。产物是管线外的（封面等），登记时加 routing:"none"。

顺带问一句看点准则：访谈里若已问出「这个栏目什么样的画面才叫有看点」（哪怕只是几条口语判据），把它写成一段纯文本落进同一份栏目配置的 broll.highlight_rubric（L2 层）。它只影响 B-roll 候选的 看点评分口径，不参与检索/过滤/剔除。配了之后该栏目跑 gtrk matrix describe 不必每次带 --highlight-rubric；单次要临时换一套，flag 会整体覆盖它（OVERRIDE，不拼接——两段准则拼起来会产出自相矛盾的评分口径）。没问出来就别硬凑，缺省走服务端领域无关准则。

交付前自检（你自己的 Quality Bar）

访谈记录里，产出 skill 的每一个组织维度，首次都是用户说出的（或从他的作品评语里直接引出的），不是我提出的？
我的提问里没有出现任何种子栏目/预设语系的概念名（用户自己先说的除外）？
卡壳追问 ≤3 条且每条有触发语记录？
产出 skill 有：触发器 description / 铁律（含禁令）/ 可判定自检清单 / exemplar 或判例计划？
契约绑定查了映射表（而不是凭记忆）？
产出 skill 是纯生产者——正文里没有任何 gtrk 命令、没有「产完接着跑…」、不碰 dispatch/struct_meta/SOP 编排（铁律 6）？
栏目配置登记是追加语义，既有条目一条没丢？
已提醒用户：skill 是他的资产，留本地即可用；上传到 agent 产品的云端 skill 市场是可选分发，非必需？

下一步（回成片管线）

建栏目是一次性装修厨房，装完就该开始做菜。栏目 skill 家族 + 词表 + 栏目配置就绪后，告诉用户「风格体系已就绪，给我一条口播毛片就能开工」，顺势回到成片管线起点：用户给毛片 → 触发 /gtrk-oralcut（agent 跑 gtrk oralcut）→ /gtrk-splitter 拆分派单 → 各车道用你刚建的生产 skill 产内容 + agent 跑 gtrk mg/matrix 铺轨 → gtrk render 出片。往后每片都在这套厨房里做，不用重新装修。agent 替用户跑 CLI，用户只对话。

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Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v8 — 11/3/2026

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LLM judge · does the skill do what it claims

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LLM judge · policy & harmful-content review

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gitruck / cli

skills/gtrk-style-maker/SKILL.md

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License MITImported 11/3/2026Version v2Bundled 3 files

Illustrative Want to see what gitruck/gtrk-style-maker 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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gtrk-style-maker · 造你自己的视觉 skill

铁律（先读，贯穿全程）

访谈工艺 · 七招

① 作品逆向（维度的出生地）

② 禁令先行（最硬的护栏都是负面的）

③ 从工序提决策树

④ 铁律化 + 自检清单

⑤ 词表沉淀

⑥ 家族切分

⑦ exemplar 优先

卡壳弹药（受铁律 2 约束）

产出工序（访谈收敛后）

交付前自检（你自己的 Quality Bar）

下一步（回成片管线）

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