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AlphaShop新品选品SKILL · leoyeai | DecimalAI

Industryby leoyeai

AlphaShop新品选品SKILL

AlphaShop新品选品SKILL：基于关键词和商品筛选条件生成深度市场分析和新品推荐报告。支持Amazon和TikTok平台的跨境电商选品，提供市场评级、竞争分析、新品推荐、热销品对比等功能。

Never made a case worse

SkillScore

SkillScore86/100

Test results 86

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

23%86%of test cases passed +64 pts

Without skill5 of 22

With skill19 of 22

14 fixed5 passed either way3 still failing0 broke

Measured on gemini-3.6-flash8/6/2026v119 comparable

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskWhat is the exact HTTP POST URL endpoint used by AlphaShop to request the new product report execution?

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 leoyeai-alphashop-sel-newproduct
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("leoyeai-alphashop-sel-newproduct")
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 leoyeai-alphashop-sel-newproduct

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/leoyeai-alphashop-sel-newproduct/SKILL.md https://app.decimal.ai/s/leoyeai-alphashop-sel-newproduct/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/leoyeai-alphashop-sel-newproduct/SKILL.md

This gets SKILL.md only. The skill's 2 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 leoyeai-alphashop-sel-newproduct

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("leoyeai-alphashop-sel-newproduct")
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/leoyeai-alphashop-sel-newproduct/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/leoyeai-alphashop-sel-newproduct/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 2 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 leoyeai-alphashop-sel-newproduct

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("leoyeai-alphashop-sel-newproduct")
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/leoyeai-alphashop-sel-newproduct/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/leoyeai-alphashop-sel-newproduct/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 2 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 leoyeai-alphashop-sel-newproduct

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("leoyeai-alphashop-sel-newproduct")
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/leoyeai-alphashop-sel-newproduct/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/leoyeai-alphashop-sel-newproduct/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 2 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 leoyeai-alphashop-sel-newproduct

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("leoyeai-alphashop-sel-newproduct")
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/leoyeai-alphashop-sel-newproduct/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/leoyeai-alphashop-sel-newproduct/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 2 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 leoyeai-alphashop-sel-newproduct

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("leoyeai-alphashop-sel-newproduct")
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/leoyeai-alphashop-sel-newproduct/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/leoyeai-alphashop-sel-newproduct/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 2 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 leoyeai-alphashop-sel-newproduct

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("leoyeai-alphashop-sel-newproduct")
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/leoyeai-alphashop-sel-newproduct/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/leoyeai-alphashop-sel-newproduct/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 2 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 leoyeai-alphashop-sel-newproduct

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("leoyeai-alphashop-sel-newproduct")
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/leoyeai-alphashop-sel-newproduct/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 2 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 leoyeai-alphashop-sel-newproduct

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("leoyeai-alphashop-sel-newproduct")
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/leoyeai-alphashop-sel-newproduct/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/leoyeai-alphashop-sel-newproduct/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 2 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 leoyeai-alphashop-sel-newproduct

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("leoyeai-alphashop-sel-newproduct")
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/leoyeai-alphashop-sel-newproduct/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/leoyeai-alphashop-sel-newproduct/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 2 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 leoyeai-alphashop-sel-newproduct

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("leoyeai-alphashop-sel-newproduct")
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/leoyeai-alphashop-sel-newproduct/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/leoyeai-alphashop-sel-newproduct/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 2 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 leoyeai-alphashop-sel-newproduct

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("leoyeai-alphashop-sel-newproduct")
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/leoyeai-alphashop-sel-newproduct/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/leoyeai-alphashop-sel-newproduct/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 2 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 leoyeai-alphashop-sel-newproduct

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("leoyeai-alphashop-sel-newproduct")
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/leoyeai-alphashop-sel-newproduct/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/leoyeai-alphashop-sel-newproduct/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 2 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 leoyeai-alphashop-sel-newproduct

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/leoyeai-alphashop-sel-newproduct/SKILL.md https://app.decimal.ai/s/leoyeai-alphashop-sel-newproduct/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/leoyeai-alphashop-sel-newproduct/SKILL.md

This gets SKILL.md only. The skill's 2 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/leoyeai-alphashop-sel-newproduct/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/leoyeai-alphashop-sel-newproduct.json

This gets SKILL.md only. The skill's 2 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 8/6/2026
Source: LeoYeAI/openclaw-master-skills ↗
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

配置

环境变量

需要配置 AlphaShop API 凭证。在 OpenClaw config 中设置：

{
  skills: {
    entries: {
      "alphashop-sel-newproduct": {
        env: {
          ALPHASHOP_ACCESS_KEY: "你的AccessKey",
          ALPHASHOP_SECRET_KEY: "你的SecretKey"
        }
      }
    }
  }
}

如何获取 API Key

获取途径

本 skill 使用 AlphaShop/遨虾平台的 API 服务，需要申请以下凭证：

ALPHASHOP_ACCESS_KEY - API 访问密钥
ALPHASHOP_SECRET_KEY - API 密钥

申请步骤

联系平台方
- 如果您是 1688 或阿里内部用户，请联系 AlphaShop/遨虾平台管理员
- 平台可能需要您提供：
  - 公司信息
  - 使用场景说明
  - 预期调用量
获取凭证
- 平台审核通过后会提供：
  - Access Key（访问密钥）
  - Secret Key（密钥）
配置到环境
- 按照上面的配置方式设置环境变量

缺少凭证时的提示

如果运行 skill 时未配置凭证，会看到详细的配置指南：

🔐 需要 AlphaShop API 凭证

本 skill 需要以下凭证才能使用：
  • ALPHASHOP_ACCESS_KEY  - API 访问密钥
  • ALPHASHOP_SECRET_KEY  - API 密钥

📋 如何获取凭证：
1. 联系 AlphaShop/遨虾 平台获取 API 凭证
2. 配置环境变量或 OpenClaw 配置
3. 重新运行命令

AlphaShop新品选品SKILL

通过遨虾AI选品API进行跨境电商市场分析和新品推荐，一次调用即可获得完整的市场洞察和选品建议。

快速开始

⚠️ 使用前必读：本 skill 包含两个 API，且有先后依赖关系！

正确的使用顺序

第一步：关键词搜索 (search)
   ↓ 返回合法的关键词列表（带 keyword 字段）
   ↓
第二步：从返回结果中选择一个 keyword 字段的值
   ↓
第三步：新品报告 (report) - 使用第一步返回的 keyword

示例：

# 1️⃣ 先搜索关键词
python3 scripts/selection.py search --keyword "phone" --platform "amazon" --region "US"

# 输出：返回关键词列表，例如：
#   1. phone (手机) - keyword: "phone"
#   2. phone case (手机壳) - keyword: "phone case"

# 2️⃣ 使用返回的 keyword 生成报告
python3 scripts/selection.py report --keyword "phone case" --platform "amazon" --country "US"

❌ 错误示例：直接使用随意关键词会报错

python3 scripts/selection.py report --keyword "随便的关键词" --platform "amazon" --country "US"
# 错误：KEYWORD_ILLEGAL - 关键词不合法

功能说明

本Skill封装了遨虾AI选品API，提供两大核心功能：

⚠️ 重要提示：这两个功能有先后顺序依赖关系！

第一步：必须先调用 关键词搜索 (search) 获取合法的关键词列表
第二步：从返回结果中选择一个 keyword 字段的值
第三步：使用该关键词作为 新品报告 (report) 的 --keyword 参数

1. 关键词搜索 (search)

通过AI关键词查询API，根据用户输入的关键词匹配并返回相关关键词列表及市场数据：

关键词推荐 - AI匹配的相关关键词列表（中英文）
机会评分 - 每个关键词的市场机会综合评分和排名
市场趋势 - 近12个月搜索排名/达人数趋势
销售数据 - 30天销量、销售额及环比增长
雷达分析 - 市场需求、供给、销售、新品、评价五维评分

2. 新品报告 (report)

⚠️ 前置依赖：此功能依赖"关键词搜索"的返回结果！

必须先执行 search 命令获取关键词列表
--keyword 参数必须使用 search 返回的 keyword 字段值
随意填写关键词会报错 KEYWORD_ILLEGAL

通过AI新品报告执行API生成深度市场分析和新品推荐：

市场分析 - 市场评级、供需情况、销售表现、竞争态势
关键指标 - 搜索排名趋势、销量趋势、价格分析、雷达图
新品推荐 - AI筛选的机会新品及详细数据
竞品对比 - 新品与同类目热销品的深度对比分析

支持的平台和国家

Amazon 平台

支持国家：US, UK, ES, FR, DE, IT, CA, JP

TikTok 平台

支持国家：ID, VN, MY, TH, PH, US, SG, BR, MX, GB, ES, FR, DE, IT, JP

使用方法

功能1：关键词搜索 (search)

基础用法

搜索关键词并获取相关关键词列表及市场数据：

python3 scripts/selection.py search \
  --keyword "yoga pants" \
  --platform "amazon" \
  --region "US"

带上架时间筛选

指定商品上架时间范围：

python3 scripts/selection.py search \
  --keyword "yoga pants" \
  --platform "amazon" \
  --region "US" \
  --listing-time "90"

参数说明

参数	类型	必填	说明	示例
`--keyword`	String	✅	查询关键词（只支持单个关键词）	`"yoga pants"`
`--platform`	String	✅	平台（`amazon` 或 `tiktok`，小写）	`"amazon"`
`--region`	String	✅	国家代码（见上方支持列表）	`"US"`
`--listing-time`	String	❌	商品上架时间范围（`"90"` 或 `"180"`，默认180天）	`"90"`
`--output-json`	Flag	❌	输出完整JSON	-

返回数据

每个关键词包含：

关键词信息
- keyword: 英文关键词
- keywordCn: 中文关键词
- platform: 平台标识（amazon/tiktok）
机会评分
- oppScore: 市场机会综合评分（数值越高机会越大）
- oppScoreDesc: 机会分解读（如"击败同一级类目85.5%关键词"）
核心指标
- searchRank: Amazon搜索排名或 TikTok带货达人数
- rankTrends: 近12个月趋势数据
销售数据
- soldCnt30d: 近30天累计销量及环比增长率
- soldAmt30d: 近30天累计销售额及环比增长率
雷达分
- Amazon: 市场需求分、市场供给分、市场销售分、新品分、评价分（5维）
- TikTok: 市场供给分、市场销售分、新品分、评价分（4维）

输出示例

============================================================
相关关键词 (10)
============================================================

1. yoga pants (瑜伽裤)
   平台: AMAZON
   机会分: 37.2 (击败同一级类目85.5%关键词)
   最新1个月亚马逊搜索排名: # 3.6k+
   30天销量: 113.7w+ (↓ -17.5%)
   30天销售额: US$2603.9w+ (↓ -18.4%)
   雷达分: 市场需求分: 41.51, 市场供给分: 47.9, 市场销售分: 45.4...

2. yoga pants set (瑜伽裤套装)
   平台: AMAZON
   机会分: 38.9 (击败同一级类目91.5%关键词)
   最新1个月亚马逊搜索排名: # 20w+
   30天销量: 34.6w+ (↑ 4.7%)
   30天销售额: US$1219.4w+ (↑ 3.4%)
   雷达分: 市场需求分: 12.86, 市场供给分: 48.7, 市场销售分: 42.5...

============================================================
关键词数据已保存到: output/alphashop-sel-newproduct/keywords-yoga-pants-US-20260312-213928.json
============================================================

功能2：新品报告 (report)

⚠️ 重要：使用此功能前，必须先调用"关键词搜索"获取合法关键词！

基础用法

生成完整的新品选品报告：

python3 scripts/selection.py report \
  --keyword "phone" \
  --platform "amazon" \
  --country "US"

带筛选条件的用法

指定商品上架时间和筛选条件：

python3 scripts/selection.py report \
  --keyword "phone" \
  --platform "amazon" \
  --country "US" \
  --listing-time "90" \
  --min-price 10 \
  --max-price 100 \
  --min-sales 1 \
  --max-sales 1000 \
  --min-rating 2.0 \
  --max-rating 5.0

参数说明

参数	类型	必填	说明	示例
`--keyword`	String	✅	⚠️ 必须从 `search` 命令返回的 `keyword` 字段获取，不可随意填写	`"phone"`
`--platform`	String	✅	平台（`amazon` 或 `tiktok`，小写）	`"amazon"`
`--country`	String	✅	国家代码（见上方支持列表）	`"US"`
`--listing-time`	String	❌	商品上架时间范围（`"90"` 或 `"180"`，默认180天）	`"90"`
`--min-price`	Number	❌	最低价格	`10`
`--max-price`	Number	❌	最高价格	`100`
`--min-sales`	Integer	❌	最低月销量	`1`
`--max-sales`	Integer	❌	最高月销量	`1000`
`--min-rating`	Float	❌	最低评分（0-5.0）	`2.0`
`--max-rating`	Float	❌	最高评分（0-5.0）	`5.0`

返回数据说明

1. 市场分析（keywordSummary）

市场评级

强烈推荐 (BEST) - 高增长、低竞争的蓝海机会
推荐进入 (GOOD) - 市场健康，有结构性机会
建议观望 (MEDIUM) - 市场平稳，需谨慎评估
不建议进入 (BAD) - 红海市场或需求萎缩

市场总结（Markdown格式）

##### 1. 市场机会总结
- 市场评级：✅推荐进入
- 市场总结：该关键词市场正处于需求强势扩张期...

##### 2. 市场情况分析
- 供给情况：在售商品数量过剩，落后于69%的同类市场...
- 需求情况：Amazon搜索排名持续提升...
- 商品销售情况：近30天销量达17.1万件...

关键指标数据

需求侧
- 搜索排名趋势（近12个月）
- 销量趋势（近12个月）
- Google Trends数据
供给侧
- 在售商品数、品牌垄断系数、商品垄断系数
- 中国卖家占比、新品销量占比
- 商品平均评分
销售表现
- 30天销量/销售额及环比增长
- 平均价格及价格带分析
雷达图
- 市场需求分、供给分、销售分、新品分、评价分

2. 新品推荐（productList）

每个新品包含：

基本信息：标题、ASIN、类目、图片、链接
价格评分：价格区间、评分、评论数
销售数据：近30天销量、近12个月销量趋势
上架信息：上架日期、上架天数
同款簇信息：同款商品数、价格范围、平均评分
对比分析：与同类目热销品的深度对比（Markdown格式）

输出示例

命令行输出

=== 市场分析 ===

市场评级: ✅推荐进入 (GOOD)
评级说明: 高增长、高客单、低新品竞争下的结构性机会

机会分: 41.7 (击败同一级类目60.5%关键词)

📊 关键指标:
- 30天销量: 17.1w+ (↑ 69.2%)
- 30天销售额: US$4170.1w+ (↑ 113.8%)
- 平均价格: US$313.27 (较高)
- 搜索排名: # 1.9k+ (BEST)
- 在售商品数: 133 (供给适中)
- 中国卖家占比: 19.3% (中低竞争)
- 新品成交占比: 0.1% (较难突围)

=== 推荐新品 (1) ===

1. Apple iPhone 17 Pro Max, US Version...
   价格: US$1449.99~US$1950.0
   评分: 4.1 ⭐ (0条评论)
   30天销量: 473件
   上架: 2025-10-09 (75天)
   同款: 12个商品
   链接: https://www.amazon.com/dp/B0FTC2PRVZ/

报告已保存到: output/alphashop-sel-newproduct/report-phone-US-20261212-143000.json

错误处理

常见错误码

错误码	说明	解决方案
`KEYWORD_ILLEGAL`	关键词不合法	使用关键词查询API返回的关键词
`TARGET_PLATFORM_ILLEGAL`	平台不合法	只能是 `amazon` 或 `tiktok`
`TARGET_COUNTRY_ILLEGAL`	国家不合法	检查国家代码是否在支持列表中
`PRODUCT_LISTING_TIME_ERROR`	上架时间参数错误	只能是 `"90"` 或 `"180"`
`PRODUCT_FILTER_PARAMS_ERROR`	筛选参数错误	检查价格/销量/评分区间是否合理
`PRODUCT_RECALL_EMPTY`	商品召回为空	放宽筛选条件（扩大价格/销量区间）
`KEYWORD_RISK_ERROR`	关键词涉及违禁	更换其他关键词
`TIMEOUT_ERROR`	请求超时	稍后重试

使用技巧

1. API 依赖关系（重要！）

⚠️ 关键词来源限制：新品报告 API 的 --keyword 参数必须来自关键词搜索 API 的返回结果！

正确的使用流程：

# 步骤1：调用关键词搜索 API
python3 scripts/selection.py search \
  --keyword "phone" \
  --platform "amazon" \
  --region "US"

# 步骤2：从返回的关键词列表中选择一个 keyword 值
# 例如返回了：
# 1. phone - keyword: "phone"
# 2. phone case - keyword: "phone case"
# 3. phone holder - keyword: "phone holder"

# 步骤3：使用选中的 keyword 调用新品报告 API
python3 scripts/selection.py report \
  --keyword "phone case"  # ⚠️ 必须是 search 返回的 keyword 字段值
  --platform "amazon" \
  --country "US"

错误示例：

# ❌ 直接使用随意的关键词（会报错 KEYWORD_ILLEGAL）
python3 scripts/selection.py report \
  --keyword "my random keyword" \
  --platform "amazon" \
  --country "US"

为什么有这个限制？

关键词搜索 API 会对关键词进行 AI 分析和校验
只有经过校验的关键词才能保证新品报告的数据质量
随意填写的关键词可能无法匹配到有效的市场数据

2. 筛选条件设置

价格区间：根据目标利润空间设置，最低价 < 最高价
销量区间：建议设置宽松范围，避免召回为空
评分区间：0-5.0，建议 minRating >= 3.0 过滤低质商品
上架时间："90" 查找最新商品，"180" 覆盖面更广

3. 报错处理

PRODUCT_RECALL_EMPTY：说明筛选条件太严，建议：
- 扩大价格区间（如 1-500）
- 放宽销量要求（如 0-10000）
- 降低评分门槛（如 0-5.0）

API 接口地址

接口	方法	URL	响应耗时
关键词搜索API	POST	`https://api.alphashop.cn/opp.selection.keyword.search/1.0`	10秒内
新品报告API	POST	`https://api.alphashop.cn/opp.selection.newproduct.report/1.0`	10秒内

注意事项

响应时间：接口响应需要几十秒，请耐心等待
无需鉴权：API为公开接口，无需配置Token
同步返回：一次调用即可获得完整报告，无需轮询
关键词限制：仅支持单个关键词，不支持多关键词组合
平台差异：Amazon和TikTok的数据结构和指标略有差异

完整示例

正确的完整工作流

# ====================================
# 步骤1：关键词搜索
# ====================================
python3 scripts/selection.py search \
  --keyword "yoga pants" \
  --platform "amazon" \
  --region "US" \
  --listing-time "90"

# 输出示例：
# 1. yoga pants (瑜伽裤) - keyword: "yoga pants"
# 2. yoga pants women (女士瑜伽裤) - keyword: "yoga pants women"
# 3. yoga pants set (瑜伽裤套装) - keyword: "yoga pants set"

# ====================================
# 步骤2：选择关键词生成新品报告
# ====================================
# ⚠️ 注意：--keyword 必须使用步骤1返回的 keyword 字段值

python3 scripts/selection.py report \
  --keyword "yoga pants set" \
  --platform "amazon" \
  --country "US" \
  --listing-time "90" \
  --min-price 15 \
  --max-price 50 \
  --min-sales 10 \
  --min-rating 3.5

# ====================================
# TikTok 平台完整示例
# ====================================

# 步骤1：搜索关键词
python3 scripts/selection.py search \
  --keyword "female dress" \
  --platform "tiktok" \
  --region "ID"

# 步骤2：生成报告
python3 scripts/selection.py report \
  --keyword "female dress"  # 使用步骤1返回的 keyword
  --platform "tiktok" \
  --country "ID" \
  --listing-time "180"

API 参考文档

完整的API接口和数据结构文档请参阅 references/api.md。

About this skill

Automatic

Sales & GTM pack

SkillSafety

✓ 3 of 3 passed

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0 critical · 0 warning · 0 info — scanner v4 — 8/2/2026

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LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

LeoYeAI / openclaw-master-skills

skills/alphashop-sel-newproduct/SKILL.md

View on GitHub ↗

License MITImported 8/2/2026Version v1Bundled 2 files · scripts

Illustrative Want to see what leoyeai/alphashop-sel-newproduct 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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Track record

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配置

环境变量

如何获取 API Key

获取途径

申请步骤

缺少凭证时的提示

AlphaShop新品选品SKILL

快速开始

正确的使用顺序

功能说明

1. 关键词搜索 (search)

2. 新品报告 (report)

支持的平台和国家

Amazon 平台

TikTok 平台

使用方法

功能1：关键词搜索 (search)

基础用法

带上架时间筛选

参数说明

返回数据

输出示例

功能2：新品报告 (report)

基础用法

带筛选条件的用法

参数说明

返回数据说明

1. 市场分析（keywordSummary）

市场评级

市场总结（Markdown格式）

关键指标数据

2. 新品推荐（productList）

输出示例

命令行输出

错误处理

常见错误码

使用技巧

1. API 依赖关系（重要！）

2. 筛选条件设置

3. 报错处理

API 接口地址

注意事项

完整示例

正确的完整工作流

API 参考文档

SkillSafety

Source

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