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shadcn/ui | DecimalAI

Frontendby shadcn

shadcn/ui

Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for "shadcn init", "create an app with --preset", or "switch to --preset".

Maintained

SkillScore

SkillScore77/100

Test results 77

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

23%77%of test cases passed +55 pts

Without skill5 of 22

With skill17 of 22

13 fixed4 passed either way4 still failing1 broke

Model 8/3/2026v2 · latest is v418 comparable

This benchmark measured an earlier version of the skill.

A newer attempt on gemini-3.8-flash on 10/18/2026 did not produce a publishable comparison (graded differently). The snapshot above is the previously measured run.

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskWhat CLI command creates a new Next.js project named `admin-portal` with monorepo configuration using the `base-nova` preset?

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 shadcn
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("shadcn")
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 shadcn

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/shadcn/SKILL.md https://app.decimal.ai/s/shadcn/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/shadcn/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 shadcn

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("shadcn")
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/shadcn/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/shadcn/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 shadcn

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("shadcn")
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/shadcn/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/shadcn/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 shadcn

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("shadcn")
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/shadcn/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/shadcn/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 shadcn

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("shadcn")
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/shadcn/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/shadcn/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 shadcn

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("shadcn")
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/shadcn/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/shadcn/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 shadcn

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("shadcn")
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/shadcn/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/shadcn/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 shadcn

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("shadcn")
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/shadcn/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 shadcn

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("shadcn")
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/shadcn/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/shadcn/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 shadcn

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("shadcn")
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/shadcn/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/shadcn/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 shadcn

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("shadcn")
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/shadcn/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/shadcn/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 shadcn

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("shadcn")
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/shadcn/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/shadcn/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 shadcn

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("shadcn")
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/shadcn/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/shadcn/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 shadcn

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/shadcn/SKILL.md https://app.decimal.ai/s/shadcn/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/shadcn/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/shadcn/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/shadcn.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: v4 (v2 tested 8/3/2026)
Source: shadcn/ui ↗
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

shadcn/ui

A framework for building ui, components and design systems. Components are added as source code to the user's project via the CLI.

IMPORTANT: Run all CLI commands using the project's package runner: npx shadcn@latest, pnpm dlx shadcn@latest, or bunx --bun shadcn@latest — based on the project's packageManager. Examples below use npx shadcn@latest but substitute the correct runner for the project.

Current Project Context

!`npx shadcn@latest info --json`

The JSON above contains the project config and installed components. Use npx shadcn@latest docs <component> to get documentation and example URLs for any component.

Principles

Use existing components first. Use npx shadcn@latest search to check registries before writing custom UI. Check community registries too.
Compose, don't reinvent. Settings page = Tabs + Card + form controls. Dashboard = Sidebar + Card + Chart + Table.
Use built-in variants before custom styles. variant="outline", size="sm", etc.
Use semantic colors. bg-primary, text-muted-foreground — never raw values like bg-blue-500.

Critical Rules

These rules are always enforced. Each links to a file with Incorrect/Correct code pairs.

Styling & Tailwind → styling.md

className for layout, not styling. Never override component colors or typography.
No space-x-* or space-y-*. Use flex with gap-*. For vertical stacks, flex flex-col gap-*.
Use size-* when width and height are equal. size-10 not w-10 h-10.
Use truncate shorthand. Not overflow-hidden text-ellipsis whitespace-nowrap.
No manual dark: color overrides. Use semantic tokens (bg-background, text-muted-foreground).
Use cn() for conditional classes. Don't write manual template literal ternaries.
No manual z-index on overlay components. Dialog, Sheet, Popover, etc. handle their own stacking.

Forms & Inputs → forms.md

Forms use FieldGroup + Field. Never use raw div with space-y-* or grid gap-* for form layout.
InputGroup uses InputGroupInput/InputGroupTextarea. Never raw Input/Textarea inside InputGroup.
Buttons inside inputs use InputGroup + InputGroupAddon.
Option sets (2–7 choices) use ToggleGroup. Don't loop Button with manual active state.
FieldSet + FieldLegend for grouping related checkboxes/radios. Don't use a div with a heading.
Field validation uses data-invalid + aria-invalid. data-invalid on Field, aria-invalid on the control. For disabled: data-disabled on Field, disabled on the control.

Component Structure → composition.md

Items always inside their Group. SelectItem → SelectGroup. DropdownMenuItem → DropdownMenuGroup. CommandItem → CommandGroup.
Use asChild (radix) or render (base) for custom triggers. Check base field from npx shadcn@latest info. → base-vs-radix.md
Dialog, Sheet, and Drawer always need a Title. DialogTitle, SheetTitle, DrawerTitle required for accessibility. Use className="sr-only" if visually hidden.
Use full Card composition. CardHeader/CardTitle/CardDescription/CardContent/CardFooter. Don't dump everything in CardContent.
Button has no isPending/isLoading. Compose with Spinner + data-icon + disabled.
TabsTrigger must be inside TabsList. Never render triggers directly in Tabs.
Avatar always needs AvatarFallback. For when the image fails to load.

Use Components, Not Custom Markup → composition.md

Use existing components before custom markup. Check if a component exists before writing a styled div.
Callouts use Alert. Don't build custom styled divs.
Empty states use Empty. Don't build custom empty state markup.
Toast follows the project base. Use toast from the toast component for Base UI projects. Use toast() from sonner for Radix and React Aria projects.
Use Separator instead of <hr> or <div className="border-t">.
Use Skeleton for loading placeholders. No custom animate-pulse divs.
Use Badge instead of custom styled spans.

Icons → icons.md

Icons in Button use data-icon. data-icon="inline-start" or data-icon="inline-end" on the icon.
No sizing classes on icons inside components. Components handle icon sizing via CSS. No size-4 or w-4 h-4.
Pass icons as objects, not string keys. icon={CheckIcon}, not a string lookup.

Chat & Messaging → chat.md

Chat UI composes the chat primitives. Conversations use MessageScroller, rows use Message, surfaces use Bubble. Never hand-rolled bubble divs or a raw scroll container.
MessageScroller owns scroll behavior. Streaming follow, anchoring, and jump-to-latest (MessageScrollerButton) are built in. Don't write a useStickToBottom/ResizeObserver hook.
Attachments use Attachment; system notes and dividers use Marker. Not Item cards or Separator + a label.
Assistant activity uses Trace. Reasoning, tool calls, sources and steps are TraceLines in a Trace, one Trace per run of message parts. Behavior wraps the line: TraceCollapsible, a sheet trigger or a link. Not a hand-rolled Collapsible or a Marker.

CLI

Never decode preset codes or build preset URLs manually. Use npx shadcn@latest preset decode <code>, preset url <code>, or preset open <code>. For project-aware preset detection, use npx shadcn@latest preset resolve.
Apply preset codes directly with the CLI. Use npx shadcn@latest apply <code> for existing projects, or npx shadcn@latest init --preset <code> when initializing.

Key Patterns

These are the most common patterns that differentiate correct shadcn/ui code. For edge cases, see the linked rule files above.

// Form layout: FieldGroup + Field, not div + Label.
<FieldGroup>
  <Field>
    <FieldLabel htmlFor="email">Email</FieldLabel>
    <Input id="email" />
  </Field>
</FieldGroup>

// Validation: data-invalid on Field, aria-invalid on the control.
<Field data-invalid>
  <FieldLabel>Email</FieldLabel>
  <Input aria-invalid />
  <FieldDescription>Invalid email.</FieldDescription>
</Field>

// Icons in buttons: data-icon, no sizing classes.
<Button>
  <SearchIcon data-icon="inline-start" />
  Search
</Button>

// Spacing: gap-*, not space-y-*.
<div className="flex flex-col gap-4">  // correct
<div className="space-y-4">           // wrong

// Equal dimensions: size-*, not w-* h-*.
<Avatar className="size-10">   // correct
<Avatar className="w-10 h-10"> // wrong

// Status colors: Badge variants or semantic tokens, not raw colors.
<Badge variant="secondary">+20.1%</Badge>    // correct
<span className="text-emerald-600">+20.1%</span> // wrong

Component Selection

Need	Use
Button/action	`Button` with appropriate variant
Form inputs	`Input`, `Select`, `Combobox`, `Switch`, `Checkbox`, `RadioGroup`, `Textarea`, `InputOTP`, `Slider`
Toggle between 2–5 options	`ToggleGroup` + `ToggleGroupItem`
Data display	`Table`, `Card`, `Badge`, `Avatar`
Navigation	`Sidebar`, `NavigationMenu`, `Breadcrumb`, `Tabs`, `Pagination`
Overlays	`Dialog` (modal), `Sheet` (side panel), `Drawer` (bottom sheet), `AlertDialog` (confirmation)
Feedback	`toast` (Base UI), `sonner` (Radix/Aria), `Alert`, `Progress`, `Skeleton`, `Spinner`
Command palette	`Command` inside `Dialog`
Charts	`Chart` (wraps Recharts)
Layout	`Card`, `Separator`, `Resizable`, `ScrollArea`, `Accordion`, `Collapsible`
Empty states	`Empty`
Menus	`DropdownMenu`, `ContextMenu`, `Menubar`
Tooltips/info	`Tooltip`, `HoverCard`, `Popover`
Chat / conversation UI	`MessageScroller`, `Message`, `Bubble`, `Attachment`, `Marker`, `Trace`

Key Fields

The injected project context contains these key fields:

aliases → use the actual alias prefix for imports (e.g. @/, ~/), never hardcode.
isRSC → when true, components using useState, useEffect, event handlers, or browser APIs need "use client" at the top of the file. Always reference this field when advising on the directive.
tailwindVersion → "v4" uses @theme inline blocks; "v3" uses tailwind.config.js.
tailwindCssFile → the global CSS file where custom CSS variables are defined. Always edit this file, never create a new one.
style → component visual treatment (e.g. nova, vega).
base → primitive library (radix or base). Affects component APIs and available props.
iconLibrary → determines icon imports. Use lucide-react for lucide, @tabler/icons-react for tabler, etc. Never assume lucide-react.
resolvedPaths → exact file-system destinations for components, utils, hooks, etc.
framework → routing and file conventions (e.g. Next.js App Router vs Vite SPA).
packageManager → use this for any non-shadcn dependency installs (e.g. pnpm add date-fns vs npm install date-fns).
preset → resolved preset code and values for the current project. Use npx shadcn@latest preset resolve --json when you only need preset information.

See cli.md — info command for the full field reference.

Component Docs, Examples, and Usage

Run npx shadcn@latest docs <component> to get the URLs for a component's documentation, examples, and API reference. Fetch these URLs to get the actual content.

npx shadcn@latest docs button dialog select

When creating, fixing, debugging, or using a component, always run npx shadcn@latest docs and fetch the URLs first. This ensures you're working with the correct API and usage patterns rather than guessing.

Workflow

Get project context — already injected above. Run npx shadcn@latest info again if you need to refresh.
Check installed components first — before running add, always check the components list from project context or list the resolvedPaths.ui directory. Don't import components that haven't been added, and don't re-add ones already installed.
Find components — npx shadcn@latest search.
Get docs and examples — run npx shadcn@latest docs <component> to get URLs, then fetch them. Use npx shadcn@latest view to browse registry items you haven't installed. To preview changes to installed components, use npx shadcn@latest add --diff.
Install or update — npx shadcn@latest add. When updating existing components, use --dry-run and --diff to preview changes first (see Updating Components below).
Fix imports in third-party components — After adding components from community registries (e.g. @bundui, @magicui), check the added non-UI files for hardcoded import paths like @/components/ui/.... These won't match the project's actual aliases. Use npx shadcn@latest info to get the correct ui alias (e.g. @workspace/ui/components) and rewrite the imports accordingly. The CLI rewrites imports for its own UI files, but third-party registry components may use default paths that don't match the project.
Review added components — After adding a component or block from any registry, always read the added files and verify they are correct. Check for missing sub-components (e.g. SelectItem without SelectGroup), missing imports, incorrect composition, or violations of the Critical Rules. Also replace any icon imports with the project's iconLibrary from the project context (e.g. if the registry item uses lucide-react but the project uses hugeicons, swap the imports and icon names accordingly). Fix all issues before moving on.
Registry must be explicit — When the user asks to add a block or component, do not guess the registry. If no registry is specified (e.g. user says "add a login block" without specifying @shadcn, @tailark, owner/repo, etc.), ask which registry to use. Never default to a registry on behalf of the user.
Switching presets — Ask the user first: overwrite, partial, merge, or skip?
- Inspect current preset: npx shadcn@latest preset resolve. Use --json when you need structured values.
- Inspect incoming preset: npx shadcn@latest preset decode <code>. Use preset url <code> or preset open <code> to share or open the preset builder.
- Overwrite: npx shadcn@latest apply <code>. Overwrites detected components, fonts, and CSS variables.
- Partial: npx shadcn@latest apply <code> --only theme,font. Updates only the selected preset parts without reinstalling UI components. Supported values are theme and font; comma-separated combinations are allowed. icon is intentionally not supported, because icon changes may require full component reinstall and transforms.
- Merge: npx shadcn@latest init --preset <code> --force --no-reinstall, then run npx shadcn@latest info to list installed components, then for each installed component use --dry-run and --diff to smart merge it individually.
- Skip: npx shadcn@latest init --preset <code> --force --no-reinstall. Only updates config and CSS, leaves components as-is.
- Important: Always run preset commands inside the user's project directory. apply only works in an existing project with a components.json file. The CLI automatically preserves the current base (base vs radix) from components.json. If you must use a scratch/temp directory (e.g. for --dry-run comparisons), pass --base <current-base> explicitly — preset codes do not encode the base.

Design Systems from DESIGN.md

When the user asks for a design system from a DESIGN.md (or a brand spec), with or without a preset, follow design-system.md end to end:

init --preset <code> --template <vite|next> --name <app> --no-monorepo -y. Without a preset code, pick the closest style and pass --base base --preset <style>. Then add --all -y.
Read the DESIGN.md frontmatter, Do's and Don'ts, and Known Gaps before editing.
Map its tokens onto the shadcn variables in tailwindCssFile. Pin the radius scale, shadows, fonts and type-* utilities.
Restyle components by editing their cva variants. Change control heights together.
Build the design system page per design-system-page.md: contrast-checked color roles, type specimens, pinned state matrices, edge cases, do/don't pairs, recipes. Check coverage with scripts/showcase-coverage.mjs.
Verify in a browser: typecheck, no console errors, loads at the top, no horizontal overflow, dark mode.

Updating Components

When the user asks to update a component from upstream while keeping their local changes, use --dry-run and --diff to intelligently merge. NEVER fetch raw files from GitHub manually — always use the CLI.

Run npx shadcn@latest add <component> --dry-run to see all files that would be affected.
For each file, run npx shadcn@latest add <component> --diff <file> to see what changed upstream vs local.
Decide per file based on the diff:
- No local changes → safe to overwrite.
- Has local changes → read the local file, analyze the diff, and apply upstream updates while preserving local modifications.
- User says "just update everything" → use --overwrite, but confirm first.
Never use --overwrite without the user's explicit approval.

Quick Reference

# Create a new project.
npx shadcn@latest init --name my-app --preset base-nova
npx shadcn@latest init --name my-app --preset a2r6bw --template vite

# Create a design system app (then follow design-system.md).
npx shadcn@latest init --name my-ds --preset b0 --template vite --no-monorepo -y
npx shadcn@latest init --name my-ds --base base --preset maia --template vite --no-monorepo -y
npx shadcn@latest add --all -y

# Create a monorepo project.
npx shadcn@latest init --name my-app --preset base-nova --monorepo
npx shadcn@latest init --name my-app --preset base-nova --template next --monorepo

# Initialize existing project.
npx shadcn@latest init --preset base-nova
npx shadcn@latest init --defaults  # shortcut: --template=next --preset=nova (base style implied)

# Apply a preset to an existing project.
npx shadcn@latest apply a2r6bw
npx shadcn@latest apply a2r6bw --only theme
npx shadcn@latest apply a2r6bw --only font
npx shadcn@latest apply a2r6bw --only theme,font

# Inspect preset codes and project preset state.
npx shadcn@latest preset decode a2r6bw
npx shadcn@latest preset url a2r6bw
npx shadcn@latest preset open a2r6bw
npx shadcn@latest preset resolve
npx shadcn@latest preset resolve --json

# Add components.
npx shadcn@latest add button card dialog
npx shadcn@latest add @magicui/shimmer-button
npx shadcn@latest add owner/repo/item
npx shadcn@latest add --all

# Preview changes before adding/updating.
npx shadcn@latest add button --dry-run
npx shadcn@latest add button --diff button.tsx
npx shadcn@latest add @acme/form --view button.tsx
npx shadcn@latest add owner/repo/item --dry-run

# Search registries.
npx shadcn@latest search @shadcn -q "sidebar"
npx shadcn@latest search @tailark -q "stats"
npx shadcn@latest search owner/repo -q "login"
npx shadcn@latest search                          # all configured registries
npx shadcn@latest search @shadcn -q "menu" -t ui  # filter by item type

# Get component docs and example URLs.
npx shadcn@latest docs button dialog select

# View registry item details (for items not yet installed).
npx shadcn@latest view @shadcn/button
npx shadcn@latest view owner/repo/item

Named presets: nova, vega, maia, lyra, mira, luma Templates: next, vite, start, react-router, astro (all support --monorepo) and laravel (not supported for monorepo) Preset codes: Version-prefixed base62 strings (e.g. a2r6bw or b0), from ui.shadcn.com.

Detailed References

rules/forms.md — FieldGroup, Field, InputGroup, ToggleGroup, FieldSet, validation states
rules/composition.md — Groups, overlays, Card, Tabs, Avatar, Alert, Empty, Toast, Separator, Skeleton, Badge, Button loading
rules/chat.md — MessageScroller, Message, Bubble, Attachment, Marker, Trace; streaming, anchoring, jump-to-latest, assistant activity rows
rules/icons.md — data-icon, icon sizing, passing icons as objects
rules/styling.md — Semantic colors, variants, className, spacing, size, truncate, dark mode, cn(), z-index
rules/base-vs-radix.md — asChild vs render, Select, ToggleGroup, Slider, Accordion
cli.md — Commands, flags, presets, templates
registry.md — Authoring source registries, include, item definitions, dependencies, GitHub registry rules
customization.md — Theming, CSS variables, extending components
design-system.md: DESIGN.md (with or without a preset) to a themed app: style picking, token mapping, radius, fonts, type scale, control heights, showcase traps, verification
design-system-page.md: What goes on a design system page and how: foundations, component tiers, pinned state matrices, contrast pairs, edge cases, do/don't, recipes

About this skill

Automatic

Frontend / UI pack

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v6 — 10/18/2026

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

shadcn / ui

skills/shadcn/SKILL.md

View on GitHub ↗

License MITImported 10/18/2026Version v4Bundled 3 files · scripts

Illustrative Want to see what shadcn 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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What it changes

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shadcn/ui

Current Project Context

Principles

Critical Rules

Styling & Tailwind → styling.md

Forms & Inputs → forms.md

Component Structure → composition.md

Use Components, Not Custom Markup → composition.md

Icons → icons.md

Chat & Messaging → chat.md

CLI

Key Patterns

Component Selection

Key Fields

Component Docs, Examples, and Usage

Workflow

Design Systems from DESIGN.md

Updating Components

Quick Reference

Detailed References

SkillSafety

Source

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