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iPolloWork 插件 UI · devin-axis | DecimalAI

Frontendby devin-axis

iPolloWork 插件 UI

为 iPolloWork 新插件或插件工作区复用 UI 组件、颜色、字体及交互规范。按 Figma 成熟状态和代码清单优先采用已确认组件，区分宿主 React 与独立 HTML/iframe 的接入方式；适用于插件表单、导航、浮层、反馈、状态和进度设计及实现，不改变用户作品的视觉风格。

Never made a case worseMaintained

SkillScore

SkillScore96/100

Test results 96

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

41%96%of test cases passed +56 pts

Without skill11 of 27

With skill26 of 27

15 fixed11 passed either way1 still failing0 broke2 errored

Measured on gemini-3.6-flash10/29/2026v129 attempted

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskWe are creating a custom SVG illustration for an iPolloWork plugin that requires using the exact brand primary color for a vector shape. The designer needs the specific hex code to use in the SVG fill attribute. What is the explicit brand primary hex color value?

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 devin-axis-ipollowork-plugin-ui
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("devin-axis-ipollowork-plugin-ui")
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 devin-axis-ipollowork-plugin-ui

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/devin-axis-ipollowork-plugin-ui/SKILL.md https://app.decimal.ai/s/devin-axis-ipollowork-plugin-ui/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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("devin-axis-ipollowork-plugin-ui")
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/devin-axis-ipollowork-plugin-ui/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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("devin-axis-ipollowork-plugin-ui")
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/devin-axis-ipollowork-plugin-ui/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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("devin-axis-ipollowork-plugin-ui")
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/devin-axis-ipollowork-plugin-ui/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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("devin-axis-ipollowork-plugin-ui")
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/devin-axis-ipollowork-plugin-ui/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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("devin-axis-ipollowork-plugin-ui")
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/devin-axis-ipollowork-plugin-ui/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/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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("devin-axis-ipollowork-plugin-ui")
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/devin-axis-ipollowork-plugin-ui/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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("devin-axis-ipollowork-plugin-ui")
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/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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("devin-axis-ipollowork-plugin-ui")
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/devin-axis-ipollowork-plugin-ui/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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("devin-axis-ipollowork-plugin-ui")
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/devin-axis-ipollowork-plugin-ui/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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("devin-axis-ipollowork-plugin-ui")
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/devin-axis-ipollowork-plugin-ui/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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("devin-axis-ipollowork-plugin-ui")
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/devin-axis-ipollowork-plugin-ui/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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("devin-axis-ipollowork-plugin-ui")
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/devin-axis-ipollowork-plugin-ui/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/devin-axis-ipollowork-plugin-ui/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 devin-axis-ipollowork-plugin-ui

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/devin-axis-ipollowork-plugin-ui/SKILL.md https://app.decimal.ai/s/devin-axis-ipollowork-plugin-ui/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/devin-axis-ipollowork-plugin-ui/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/devin-axis-ipollowork-plugin-ui/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/devin-axis-ipollowork-plugin-ui.json

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

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 10/29/2026
Source: devin-axis/ipollowork ↗
License: NOASSERTION

Manage it in DecimalAI

Saved prompts and skills, pinned versions, and traces of this skill in your runs. DecimalAI does not run your agent.

Claude Code reads files from your project, so DecimalAI config does not apply there.

On Claude Agent SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI Agents: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Anthropic: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Gemini API: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On LangChain: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On CrewAI: set DECIMAL_API_KEY and add decimalai.init(crewai=True) to record runs and skill use. The skill version stays in your repo.

On Google ADK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Pydantic AI: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Deep Agents: set DECIMAL_API_KEY and add decimalai.init(langchain=True) to record runs and skill use. The skill version stays in your repo.

On Microsoft Agent Framework: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

On Strands: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

Editors read files from your project, so DecimalAI config does not apply there.

Anywhere else: record a use with decimalai.log_skill_activation() inside a trace.

Use this skill

SKILL.md

iPolloWork 插件 UI

从用户要完成的操作选择组件。默认采用“已实现与推荐使用”，保持明确的当前值、反馈位置、恢复动作和键盘焦点。

先确定运行环境

宿主 React 页面：从 apps/app/src/components/ui 导入基础控件；@/ 是主应用别名。业务组合参考现有调用，不把领域内部组件作为插件公开 API。
独立 HTML / iframe / 独立构建的 React 插件：读取插件接入契约。主应用别名和 CSS 不会自动进入 iframe；采用现有插件的桥接方式与相同交互语义。独立 React 构建也不能假定能导入宿主组件。
共享实现位于已有 @ipollowork/ui 包。@ipollowork/ui/core 为基础组件公共汇总入口，具体模块及 Figma 对照读取组件映射。iframe 从运行时对象取得相同具名组件，通过 React 岛接入；只有 Button/Input/Textarea 支持原生 HTML 标记适配。

固定接入规则 · v1

实施插件前必须读取插件接入契约的公共入口、构建/注入和版本章节，按以下边界选择：

宿主 React 使用原有 @/components/ui/* 入口；共享包控件入口为 @ipollowork/ui/controls。
iframe 插件只从 @ipollowork/ui/runtime-contract 导入 requireRuntime(1)；实际 React/控件从返回的运行时对象取得。不要从 plugin-runtime 或宿主私有路径导入实现，也不要给生产插件再打包 React。
开发构建显式选择 buildPluginRuntime('bundled')，将运行时放在业务脚本之前；生产包不包含运行时，保留契约中的固定 meta 标记，由宿主注入。不能仅凭 NODE_ENV 推断加载方式。
当前运行时版本为 1.8.0。使用本轮颜色与字体规范时调用 requireRuntime(1, required, 3)，第三参数检查最低 minor；使用公共 Icon 时调用 requireRuntime(1, ['Button', 'Icon'], 4)，尺寸 S/M/L 为14/16/20px，Button 前后图标直接作为 children 组合，纯图标按钮必须有 aria-label。required 列出实际使用的全部函数导出（包括子组件）。共享 Badge 的 info/success/warning 语义变体和前置图标组合要求 requireRuntime(1, ['Badge', 'Icon'], 5)。SearchField、NumberField、Slider、Calendar、DatePicker / TimeInput、FileUpload / FileUploadItem 要求 requireRuntime(1, required, 6)；日期使用本地年月日，上传状态由业务调用方提供，不伪造进度或取消能力。表格组合 TableSortHead / TablePagination / TablePageSelection / TableBulkActions 要求 requireRuntime(1, required, 7)。排序、过滤、分页与稳定ID选择由调用方管理；表头只选当前页，翻页保留选择，改变筛选清空选择；批量确认与部分失败恢复必须由实际业务处理。资源卡 Card variant="resource"、CardIcon、CardMeta 和 CardTitle as="h3" 要求 requireRuntime(1, required, 8)；既有 default/outline Card 行为不变。旧版本或缺组件时停止初始化并提示更新客户端。不支持完整 semver 范围、最低 patch 或 manifest UI 版本协商，也不自动下载另一份组件库。

历史1.2整合记录不代表当前发布状态。当前core汇总43个模块；Figma推荐页的62个条目包含变体和内容示例，不能当作独立组件数量。按组件目录分别核对代码可用、业务采用、设计对齐、交互验收、发布验证五个维度。核心样板是浏览器隔离验证，真实客户端安装证据另记；签名包上传、打包客户端和跨客户端升级仍未完成全面验收。

选择顺序与证据

读取组件目录中任务涉及的条目，然后打开真实源码、导出和调用场景。

实施前按共享包README的固定验收矩阵列出本次适用状态。每条结果绑定动作、可观察断言与截图；未测状态记录Incomplete，不能由“推荐”或Figma身份自动升级为Passed。视频工作台保留专业布局，仅复用语义主题与基础控件；展开脚本隐藏属性、收起恢复原页签须单独验收。

推荐：默认复用对应代码；推荐范围以清单中的证据为限。
待验证：已有实现，先检查清单中的缺陷和边界。已复现缺陷不得默认采用；需要修复并重跑对应失败回归。没有已知缺陷时，场景匹配才可采用，并补齐本次使用的状态、主题、键盘和恢复验证。
候选：Figma 设计或待统一模式；先明确交互和代码接入，再验证。不要以存在设计稿推断存在公共组件。
历史：使用替代入口；兼容封装的迁移范围由实际调用决定。

Figma 状态页展示现有组件实例副本；主组件留在完整目录。查看设计时按需读取链接，避免把未确认的最新编辑自动升级为强制规范。源码与设计发生差异时记录双方依据，并解决影响本次任务的差异。

共享控件身份读取组件映射：主组件 ID、源码、包导出与接入方式对应。Select、Dialog、Toast 已于 2026-10-10 核对主组件及完整目录/推荐页实例引用。Toast 设计卡片对应 Toaster 容器与 toast 调用 API，不是三个独立设计组件；新增三组没有原生 HTML 标记适配。身份核对不等于全部视觉状态一致。此清单是 Code Connect 不可用时的仓库契约，不是假冒 Code Connect 发布记录。

颜色与字体

设计或实现插件页面时读取主题与 Token：以用户提供的紧凑UI表和Teal品牌色板为设计目标，按语义选择颜色与文字层级，不把当前源码遗留值当成已确认规范。Page Title16/24、Section Title14/20、Control13/18、Body13/20、Meta12/18、Caption11/16、Micro10/14的用途与字重，以及真实源码入口、差异和迁移边界均在契约中维护。字体先复用公共sans/mono栈；品牌展示页的Syne大标题不自动套入客户端UI。

品牌 Primary 为青色 #1FBAC0；普通主要按钮（Button default）浅色黑底白字、暗色青底黑字；危险按钮保留 destructive。共享层维护 --brand-*、--action-*、可读链接 --primary-text 与焦点 --ring，调用方不复制 hex。七档 text-ui-page-title/section-title/control/body/meta/caption/micro 已实际生成在运行时中，也可直接使用 --ui-{角色}-size/line 的 px 变量。字号不依赖插件根字号换算；系统字体栈不变。Field 统一留 --field-hint-gap:8px，不再给说明文字负 margin。短片工作台根字号为16px、正文13/20；iframe仍不自动继承宿主 body 和 CSS 缩放回退，不修改作品字体。

此规范不影响视频、图片、文章、演示等用户作品。代码、Figma与Skill的同步状态分别记录；目前页面级字体迁移和完整Figma文字样式对照尚未完成，不能用控件验收替代。

交互约束

完整产品规则读取仓库 docs/interaction-guidelines.zh-CN.md 中相关章节；docs/client-interactions.zh-CN.md 描述现状。遵守以下默认决策：

标准组合见共享包 README：Field 的 vertical/horizontal/responsive、InputGroup 的单位/多行字数、Button 与菜单/筛选。附件放在输入之后；纯文字附件不增加 Tab 停靠，点击附件可聚焦 Input 或 Textarea。动作分组使用命名 role=group，未实现方向键漫游时不标 role=toolbar。专业编辑布局保留。
表单组合 FieldLabel → 控件 → FieldDescription / FieldError；标签不能只靠 placeholder。错误关联字段并设置 aria-invalid，提交失败保留输入。
普通单选用 Select，需要搜索用 Autocomplete，少量需要比较的选项用 RadioGroup，多选用 Checkbox，即时开关用 Switch，工具模式用 ToggleGroup，内容切换用 Tabs。
局部轻量操作用 Popover，短表单用 Dialog，长编辑用 Sheet，高风险确认优先复用 ConfirmModal / AlertDialog。关闭恢复焦点；丢弃草稿说明后果。
短操作反馈用 Toast；字段错误、预览失败、等待授权、长期任务状态在原位置持续显示。成功 Toast 不替代交付验收。
Alert / Toast 使用无边框、无投影的语义浅背景；信息、成功、警告、错误分别使用共享 --feedback-*-background，暗色切换为低亮度背景。保留文字、状态图标和恢复动作，不另加语义边框或左侧竖条。具体 API、Token 与迁移检查读取插件接入契约。
异步反馈组合见共享包 README：首次加载才用 Skeleton；刷新保留最后确认内容与输入；只有成功空响应才展示 Empty，筛选无匹配提供清除，真实空列表提供创建/导入。失败在原位置用 Alert + AlertAction 重试；重试保留同一文件/草稿并防止重复请求。成功后按返回数据更新，不新增另一套状态机。
预览覆盖加载、空、可用、失败；刷新尽量保留上一份可用内容，失败就地重试。
分清执行状态和工作项状态：执行已结束不等于已验收；只有用户确认后才标为已验收。
真实数值才报告真实百分比；预计值显式标“预计”，不能单凭计时完成任务；无法估算时用不定进度或阶段文案。
默认复用现有尺寸和主题。普通 Input / Button 默认 32px，主动作可使用已有 36px 大尺寸；设置作用域 Button 为 28px，沿用现有 Provider。尺寸由源码决定，避免每页重新覆盖。
弹窗关闭复用 DialogContent 默认关闭控件：ghost、28px 点击区、16px 居中图标、顶部/末端12px；保留可见键盘焦点。选中只改颜色，不改文字字号、行高、尺寸或 padding；装饰伪元素绝对定位，不能占 flex gap。模板筛选复用共享 Button 与 DropdownMenu，不能单独手写原生触发器。
信息、成功、错误反馈使用语义 palette 第2档；警告使用 --project-dialog-notice 浅暖灰底（暗色为 --gray-3），不再使用黄色底。亮暗值均由共享 Token 切换。工作区模型选择不带前置图标，窄容器仍保留截断名称及下拉箭头，不能变成空按钮。
使用文字、图标或可访问名称表达状态；验证窄容器、长文案、亮暗主题与键盘使用。

实施与完成

按仓库 AGENTS.md 的演示、隔离工作区和真实体验验证流程完成可见实现；代码变更使用 ipollowork-maintainable-code，本 Skill 不重复定义代码质量规则。

检查实际控件状态、选择值、关闭与焦点、异步失败后的输入保留、重试、宿主主题更新和容器缩放。生成真实体验证据；夹具、模拟传输和真实服务链路分别报告。

本 Skill 文档更新本身可做结构、路径和链接检查；文档通过不表示插件已接入或运行验收通过。

核心公共调用样板为 evals/support/shared-ui-core-fixture.mjs，两种加载方式的体验验证为 evals/flows/shared-ui-core.flow.mjs。以真实具名导出及其 TypeScript Props 编写组合，不凭 Figma 展示标题猜测 API。AlertDialogAction 不自动关闭，异步操作成功后由调用方更新 open；失败保留弹窗。Alert 的 closeLabel、Image 的 showFullLabel/showLessLabel 由插件提供本地化文本。

完整业务接入参考 examples/plugin-packages/short-video-studio/src/ui.mjs，七页验收流程为 evals/flows/short-video-shared-ui.flow.mjs：标记适配基础输入与按钮，React 岛挂载选择、多选、导航及反馈。迁移还需移除被替代的控件 CSS，保留领域布局，避免只给旧 DOM 换颜色。不要把 Base UI 的隐藏表单 input 当作未迁移的可见控件；校验真实选择值、草稿保留和重试写盘。

资源卡复用 · runtime 1.8

目录资源复用 Card variant="resource" 的两种正式形态：surface="plain" 无边框款默认透明、hover浅灰；surface="outline" 描边款为默认值，透明底、1px语义描边、hover强调描边。两款均无阴影，圆角12px、padding16px、gap12px，右侧动作使用outline Button。内部 Header/Content/Footer 不重复padding，Header以flex排列32px透明对齐槽的CardIcon（内部Logo为24px，Lucide笔画1.5px）和正文，Footer支持左状态/右动作、换行与mt-auto，不强制高度。CardTitle可设 as="h3"（默认div保持兼容），resource内使用sans 14/20/600，CardDescription为12/18/400，CardMeta为11/16/400。尺寸按固定px，不随iframe根字号缩小。

layout="row"仅用于resource紧凑目录行（默认stack）：Header放32px图标槽（内部24px图标）、名称和一句说明并自适应占宽，最小宽度min(100%,240px)；Footer操作靠右，空间不足自然换到右下。内容/meta块可省略，不设固定卡高、不用JS测宽。普通default/outline不受layout影响。

保留资源自己的类型、来源、状态和业务回调，不伪造插件manifest套用插件业务组件；整卡不再嵌套一层button，真实动作仍用共享Button。宿主从原card入口导入，iframe required必须列出实际使用的Card及子槽并检查最低minor8。此轮是代码扩展，未新增或确认Figma身份；交互、业务采用与发布验证仍按各自证据记录。

维护

组件晋升时同时更新代码位置、Figma 状态页、清单和验证范围。主组件视觉在 Figma 完整目录维护；状态页元数据和本地目录为核对快照，不具备自动同步。新增公共组件必须有真实需求；候选库可持续编辑。

插件和技能的紧凑目录使用 Card variant="resource" layout="row" surface="plain"：默认透明无边框，悬停使用共享 muted 浅灰背景，操作使用 outline Button；其他资源卡保持默认描边。

About this skill

Automatic

Frontend / UI pack

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0 critical · 0 warning · 0 info — scanner v8 — 10/29/2026

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Source

Imported

devin-axis / ipollowork

.codex/skills/ipollowork-plugin-ui/SKILL.md

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License NOASSERTIONImported 10/29/2026Version v1Bundled 3 files

Illustrative Want to see what devin-axis/ipollowork-plugin-ui 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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iPolloWork 插件 UI

先确定运行环境

固定接入规则 · v1

选择顺序与证据

颜色与字体

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实施与完成

资源卡复用 · runtime 1.8

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