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Content Collector — 个人内容收藏系统 · leoyeai | DecimalAI

Productivityby leoyeai

Content Collector — 个人内容收藏系统

个人内容收藏与知识管理系统。收藏、整理、检索、二创。

SkillScore

SkillScore70/100

Test results 70

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

30%70%of test cases passed +39 pts

Without skill7 of 23

With skill16 of 23

10 fixed6 passed either way6 still failing1 broke

Measured on gemini-3.6-flash8/8/2026v120 comparable

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test task当收藏的内容匹配到了公众号选题池中存在的某个特定选题时，系统应该将素材交接信息追加写入哪一个具体的交接 Markdown 文件中？

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-content-collector
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-content-collector")
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-content-collector

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-content-collector/SKILL.md https://app.decimal.ai/s/leoyeai-content-collector/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/leoyeai-content-collector/SKILL.md

This gets SKILL.md only. The skill's 8 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-content-collector

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-content-collector")
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-content-collector/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-content-collector/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 8 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-content-collector

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-content-collector")
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-content-collector/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/leoyeai-content-collector/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 8 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-content-collector

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-content-collector")
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-content-collector/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/leoyeai-content-collector/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 8 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-content-collector

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-content-collector")
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-content-collector/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/leoyeai-content-collector/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 8 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-content-collector

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-content-collector")
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-content-collector/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-content-collector/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 8 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-content-collector

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-content-collector")
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-content-collector/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/leoyeai-content-collector/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 8 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-content-collector

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-content-collector")
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-content-collector/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 8 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-content-collector

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-content-collector")
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-content-collector/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/leoyeai-content-collector/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 8 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-content-collector

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-content-collector")
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-content-collector/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/leoyeai-content-collector/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 8 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-content-collector

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-content-collector")
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-content-collector/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/leoyeai-content-collector/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 8 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-content-collector

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-content-collector")
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-content-collector/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/leoyeai-content-collector/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 8 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-content-collector

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-content-collector")
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-content-collector/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/leoyeai-content-collector/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 8 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-content-collector

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-content-collector/SKILL.md https://app.decimal.ai/s/leoyeai-content-collector/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/leoyeai-content-collector/SKILL.md

This gets SKILL.md only. The skill's 8 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-content-collector/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/leoyeai-content-collector.json

This gets SKILL.md only. The skill's 8 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 8/8/2026
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

Content Collector — 个人内容收藏系统

收藏好内容 → 结构化整理 → 关键词检索 → 二次创作

数据位置

主存储（AI 检索用）

<WORKSPACE>/collections/

collections/
├── articles/       # 文章、博客、长文
├── tweets/         # X/Twitter 推文、短内容
├── videos/         # 视频内容（转录+笔记）
├── wechat/         # 微信公众号文章
├── ideas/          # 零散想法、灵感
├── index.md        # 全局索引（自动维护）
└── tags.md         # 标签索引（自动维护）

Obsidian 同步（人工浏览用，可选）

<YOUR_OBSIDIAN_VAULT>/收藏/

收藏/
├── 文章/           # ← collections/articles
├── 视频/           # ← collections/videos
├── 推文/           # ← collections/tweets
├── 公众号/         # ← collections/wechat
└── 想法/           # ← collections/ideas

每次收藏时必须同时写入两个位置。 Obsidian 版本的差异：

文件名：用中文标题（从 frontmatter title 取），不用 YYYY-MM-DD-slug 格式
标签：frontmatter 保留 tags 数组 + 正文第一行加 #tag1 #tag2 ... 格式（Obsidian 图谱和搜索用）
aliases：frontmatter 加 aliases: [title]，方便 Obsidian 双链搜索
目录映射：articles→文章、videos→视频、tweets→推文、wechat→公众号、ideas→想法

Obsidian 写入模板（伪代码）：

target_dir = <YOUR_OBSIDIAN_VAULT>/收藏/{中文目录}/
filename = sanitize(title).md   # 去掉 <>:"/\|?* 等非法字符，截断80字符
content = 原始 frontmatter（加 aliases） + "\n\n" + "#tag1 #tag2 ..." + "\n\n" + body

收藏工作流

Supadata API（优先方案）

对于大部分 URL，优先使用 Supadata API 解析：

脚本：SUPADATA_API_KEY=<key> python3 scripts/supadata_fetch.py <command> <url>
环境变量：SUPADATA_API_KEY 存放在 TOOLS.md

内容类型	命令	说明
网页/博客	`web <url>`	返回 Markdown 正文，1 credit
视频转录	`transcript <url> --text [--lang zh]`	YouTube/TikTok/X/Instagram/Facebook，1-2 credits
社交媒体元数据	`metadata <url>`	标题、作者、互动数据，1 credit

Supadata 不可用时的降级方案：

网页 → web_fetch
B站 → 本地 bilibili 脚本（见下方）
需登录/内网 → Chrome Relay

URL 内容（文章/博客/网页）

优先 supadata_fetch.py web <url> 抓取正文
降级 web_fetch 抓取正文
提取标题、作者、发布日期、正文摘要、关键词
提取有价值的插图（默认执行，见下方「插图保存规范」）
生成 collections/articles/YYYY-MM-DD-slug.md（含插图引用）
HTML 快照保存（仅重要文章）：对 P0/P1 级别的文章，额外保存一份原始 HTML 到 collections/articles/YYYY-MM-DD-slug.html，防止源页面删除后内容丢失。普通收藏不保存快照（避免磁盘膨胀）
同步到 Obsidian → <YOUR_OBSIDIAN_VAULT>/收藏/文章/{标题}.md（含插图复制）

视频内容（YouTube/TikTok/X/Instagram/Facebook）

元数据: supadata_fetch.py metadata <url>
转录: supadata_fetch.py transcript <url> --text --lang zh
内容提取：基于转录文本提取核心观点、金句、要点
生成 collections/videos/YYYY-MM-DD-slug.md
同步到 Obsidian → <YOUR_OBSIDIAN_VAULT>/收藏/视频/{标题}.md

纯文本/截图

截图用 image 工具提取文字
整理成结构化格式，来源可选补充

B站视频（本地流程，Supadata 不支持 B站）

元数据：python3 scripts/bilibili_extract.py <bvid_or_url> → 标题、作者、时长、标签、数据指标
评论区：
- 无登录（API）：3条热门
- 已登录（浏览器 shadow DOM）：20+条，见 references/bilibili-comments.md
视频转录：bash scripts/bilibili_transcribe.sh <bvid_or_url> [model]
- 依赖：yt-dlp、faster-whisper（uv）、opencc
- 需浏览器已登录B站（yt-dlp 读取 cookie）
- 模型：tiny/base(默认)/small/medium，base 约10-15分钟转录46分钟视频
- 输出：/tmp/bilibili_audio/<BVID>_transcript.json + .txt
- 注意：ASR 有识别错误，专有名词需人工校验
- 降级方案（转录失败时）：
  - yt-dlp cookie 过期 → 提示用户在 openclaw browser 重新登录 B站
  - faster-whisper 不可用 → 尝试 whisper CLI（pip3 install openai-whisper）
  - 全部失败 → 仅保存元数据+评论，在收藏文件中标注"转录未获取，待补充"，不阻塞收藏流程
内容提取：基于转录文本提取核心观点、金句、要点
生成 collections/videos/YYYY-MM-DD-slug.md
同步到 Obsidian → <YOUR_OBSIDIAN_VAULT>/收藏/视频/{标题}.md

插图保存规范

收藏文章时默认提取有价值的插图，作为后续写作素材。

判断标准（哪些图值得保存）

✅ 架构图、流程图、框架图、对比图、数据可视化
✅ 概念说明图、示意图、信息图
❌ 装饰性 banner、logo、头像、广告
❌ 纯文字截图（直接引用文字更好）

操作流程

发现插图：用 browser evaluate 提取页面 <img> 列表（src + alt + caption）
筛选：排除装饰性图片（logo、小于 200px、SVG 图标等）
下载：用 CDN 原始 URL（避免 Next.js 等图片优化层），curl -sL 保存到：
- collections 路径：collections/{category}/images/{slug}/01-描述.png
- slug 与收藏文件的文件名 slug 一致
嵌入收藏文件：在正文中用 ## 插图 章节，每张图包含：
- ![alt](images/{slug}/filename.png)
- 斜体说明文字（来自 caption 或自行总结）
同步到 Obsidian：
- 复制图片到 <YOUR_OBSIDIAN_VAULT>/收藏/{中文目录}/images/{slug}/
- Obsidian 版本使用相同的相对路径引用

命名规范

文件名：{序号}-{简短英文描述}.png（如 01-architecture-overview.png）
目录名：与收藏文件 slug 一致（如 evals-for-agents）

注意

图片保存为本地副本，不依赖外部 URL（防止链接失效）
单篇文章通常 3-8 张有价值的图，不要过度收集

关联项目（自动匹配）

每次收藏内容后，自动将内容与当前活跃项目关联：

读取 <WORKSPACE>/memory/topics/projects.md 获取活跃项目列表
将收藏内容的标题、摘要、标签与每个项目的关键词匹配

匹配到的项目写入收藏文件的 YAML frontmatter：

related_projects: ["wemp-ops", "xiaohongshu-ops"]
project_notes: "这个案例可以用于公众号选题：AI调度人力的真实案例"

同时在 index.md 中标注关联项目，方便按项目筛选素材

项目关键词（自动从 projects.md 提取）

wemp-ops：公众号、写作、文章、排版、内容运营
xiaohongshu-ops：小红书、笔记、种草、配图、短内容
content-collector：收藏、知识管理、素材库

使用场景

写公众号文章前：搜索关联 wemp-ops 的收藏 → 快速找到素材
写小红书前：搜索关联 xiaohongshu-ops 的收藏 → 找到适合拆解的内容
选题会议：按项目汇总最近收藏 → 发现选题方向

存储格式

文件命名：YYYY-MM-DD-slug.md

---
title: "标题"
source: "来源平台"
url: "原始链接"
author: "作者"
date_published: "发布日期"
date_collected: "收藏日期"
tags: [tag1, tag2, tag3]
category: "articles|tweets|videos|wechat|ideas"
language: "zh|en"
summary: "一句话摘要"
# 视频专属（可选）
duration: "时长"
platform: "bilibili|youtube"
bvid: "BV号"
stats: { views: 0, likes: 0, comments: 0 }
---

内容结构

内容概览（条件触发，见下方规则）— Mermaid 图，一图看懂全文
核心观点 — 3-7个要点
要点摘录 — 原文金句（blockquote）
热门评论精选（视频类）— 含点赞数
评论区观点摘要（视频类）— 总结争议点
我的笔记 — 用户个人批注，后续补充
原文摘要 — 200-500字概要

英文内容翻译规范

当 language: en 时，收藏过程中的翻译遵循以下规则：

翻译风格（默认 storytelling，不需要每次询问）：

风格	效果	适用
`storytelling`	叙事流畅，过渡自然（默认）	博客、观点文、技术分享
`technical`	精准简洁，术语密集	API 文档、技术规范
`conversational`	口语化，像朋友聊天	Twitter thread、播客转录、访谈
`formal`	正式结构化	学术论文、白皮书

触发条件：老板说"精翻"→ 用更仔细的翻译；说"学术风格"→ formal；默认不问直接用 storytelling。

术语表：翻译时参照 <WORKSPACE>/references/glossary-ai-zh.md 统一术语。首次出现的术语用 中文（English） 格式。

欧化检查：翻译后扫一遍欧化中文问题（多余连接词/被动语态/名词堆砌），参照 wemp-ops/references/style-guide.md 的"欧化中文自检"。

内容概览图生成规则

触发条件：正文 > 1000 字的 articles / wechat / videos（短推文、零散想法不画）。

输出格式：Mermaid 代码块，直接嵌入收藏文件的 ## 内容概览 章节。Obsidian 原生渲染，不需要额外插件。

图表类型自动选择（按文章内容匹配）：

文章特征	图表类型	Mermaid 语法	示例
方法论/框架/模型（分层、组件）	思维导图	`mindmap`	"AI PM 的 3 个核心能力"
流程/步骤/演进（先后顺序）	流程图	`graph TB`	"AI 编程三次进化"
对比/选择（A vs B）	对比图	`graph TB` + 并行 subgraph	"传统 PM vs AI PM"
多实体互动/依赖关系	关系图	`graph LR`	"Agent 各模块数据流"
时间线/里程碑	时间线	`graph LR` 线性	"2024 AI 大事记"
混合/不确定	思维导图	`mindmap`（万能兜底）	—

生成要求：

节点文字用文章原始术语，不用"概念1"、"模块A"等占位符
层级不超过 3 层——图是辅助理解，不是完整复述
节点数量 5-15 个——太少没信息量，太多一眼看不完
遵守 Mermaid 语法规范——详见 references/mermaid-syntax-rules.md，特别注意：
- 1. 触发列表解析错误 → 用 ① 或 (1) 或去掉空格
- subgraph 带空格 → 用 subgraph id["显示名"] 格式
- 节点引用用 ID 不用显示文本
- 不要在节点文本中使用 Emoji
配色使用语义色：
- 核心概念：fill:#d3f9d8,stroke:#2f9e44（绿）
- 问题/挑战：fill:#ffe3e3,stroke:#c92a2a（红）
- 方法/工具：fill:#e5dbff,stroke:#5f3dc4（紫）
- 输出/结果：fill:#c5f6fa,stroke:#0c8599（青）

嵌入格式示例：

## 内容概览

\`\`\`mermaid
mindmap
  root((AI PM 核心能力))
    问题定义
      从模糊需求到精确问题
      判断什么值得做
    上下文质量
      Context Engineering
      给 Agent 正确的信息
    判断力
      评估 Agent 产出
      知道何时人工介入
\`\`\`

不做什么：

不生成独立图片文件——Mermaid 文本直接嵌入 Markdown
不画太复杂的图——收藏文件的图是"速览"，不是完整笔记

Obsidian 同步规范

每次写入 collections/ 后，必须同时写入 Obsidian 版本。步骤：

从刚写入的收藏文件读取 frontmatter
构建 Obsidian 版本：
- 保留 frontmatter 的 title, source, url, author, date_published, date_collected, category, language, summary, duration, platform, bvid, tags
- 添加 aliases: [title]
- 正文第一行加 #tag1 #tag2 ...（标签中的空格替换为 _）
文件名 = sanitize(title).md（去掉 <>:"/\|?*，截断 80 字符）
写入到 <YOUR_OBSIDIAN_VAULT>/收藏/{中文目录}/

目录映射：

collections 目录	Obsidian 目录
articles/	文章/
videos/	视频/
tweets/	推文/
wechat/	公众号/
ideas/	想法/

注意：Obsidian 版本是 collections 的只读镜像。编辑应在 collections 原文件上进行，然后重新同步。

索引

每次收藏后更新：

index.md — 按月份倒序，含标签和来源
tags.md — 按标签聚合所有收藏

检索

标签匹配：tags.md 中查找
全文搜索：grep -ril "keyword" collections/
返回匹配列表 + 摘要

二创 — 小红书内容生成

按选题/标签从收藏库筛选素材
参考 references/xiaohongshu-style.md 写作风格
生成：emoji标题 + 口语化正文(300-800字) + 话题标签(5-10个)
发布配合 xiaohongshu-ops 技能

联动 — 公众号写作供料

收藏库是 wemp-ops 公众号写作的素材来源之一。wemp-ops 选题时会自动检索收藏库：

标签匹配：tags.md 按关键词查找相关收藏
全文搜索：grep -ril 搜索 collections/ 目录
收藏文件中的"核心观点"、"要点摘录"、"我的笔记"可直接用于文章引用

收藏时的写作友好建议：

summary 写清楚，便于快速判断是否相关
tags 覆盖主题关键词，提高检索命中率
"我的笔记"多写自己的思考和联想，这些是文章的独特视角

分类规则

来源	目录	备注
博客/网页	`articles/`	默认归类
X/Twitter	`tweets/`	短内容/thread
微信公众号	`wechat/`	中文长文
B站/YouTube/抖音	`videos/`	B站可自动转录
零散想法	`ideas/`	非外部来源

标签规范

中文为主，英文专有名词保持英文
每条 3-8 个标签
常用：AI、产品设计、电商、运营、技术、商业、创业、效率工具、思维模型、管理

写作素材交接（Skill Handoff）

收藏完成后，检查内容是否与选题池中的选题相关：

读 <WORKSPACE>/collections/topics/topic-pool.md（公众号）和 <WORKSPACE>/collections/topics/xhs-topic-pool.md（小红书）

如果收藏内容的标签/主题与某个选题匹配，追加到 <WORKSPACE>/temp/handoffs/collector-to-writing.md：

### <收藏标题>
- 关联选题：<匹配到的选题>
- 来源：<URL>
- 收藏时间：<日期>
- 可用角度：<这个素材可以怎么用在文章里，1-2句话>

追加模式（append），不覆盖已有内容
如果没有匹配的选题，跳过此步（不创建空文件）

注意：此步骤是补充性的，不替代已有的"关联项目"功能。交接文件面向下游写作 skill，关联项目面向收藏库内部检索。

命令速查

用户说	动作
"收藏这个 [URL/文字]"	抓取→整理→存储→更新索引
"搜索 [关键词]"	搜索收藏库
"最近收藏了什么"	读 index.md
"关于 [标签] 的收藏"	从 tags.md 筛选
"用 [选题] 写篇小红书"	二创生成
"给这篇加个笔记"	更新"我的笔记"部分
"删除这条收藏"	移除并更新索引 + 删除 Obsidian 对应文件
"重新同步到 Obsidian"	全量重新同步：`python3 scripts/sync_to_obsidian.py`（skill 目录下）

When it activates

Automatically, when a task matches. Use when: (1) 用户分享链接/文字/截图并要求保存或收藏, (2) 用户说"收藏这个"/"存一下"/"记录下来"/"save this"/"bookmark"/"clip this", (3) 用户要求按关键词/标签搜索之前收藏的内容, (4) 用户要求基于收藏内容生成小红书/社交媒体文案（二创/改写/洗稿）, (5) 用户发送 URL 并要求提取/总结/摘要内容, (6) 用户提到"之前看过一个..."/"上次收藏的..."等回忆性检索, (7) 用户转发或粘贴了一段内容（文章片段/推文/视频链接）并暗示想留存。即使用户没有明确说"收藏"，只要涉及保存外部内容、整理知识、检索历史收藏、或基于已收藏内容进行二次创作，都应使用此技能。已支持来源：博客、X/Twitter、网页、B站视频。内容类型：文字、长视频（B站可自动转录）、短视频。

About this skill

Automatic

Knowledge Management pack

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

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

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

LeoYeAI / openclaw-master-skills

skills/content-collector/SKILL.md

View on GitHub ↗

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

Illustrative Want to see what leoyeai/content-collector would put in front of your model? Preview the rendered body and check its trigger phrases — no LLM call, no signup.

Related skills

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From the same source and nearby in the catalogue.

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SkillScore

Safety

What it changes

Track record

Use this skill

Content Collector — 个人内容收藏系统

数据位置

主存储（AI 检索用）

Obsidian 同步（人工浏览用，可选）

收藏工作流

Supadata API（优先方案）

URL 内容（文章/博客/网页）

视频内容（YouTube/TikTok/X/Instagram/Facebook）

纯文本/截图

B站视频（本地流程，Supadata 不支持 B站）

插图保存规范

判断标准（哪些图值得保存）

操作流程

命名规范

注意

关联项目（自动匹配）

项目关键词（自动从 projects.md 提取）

使用场景

存储格式

内容结构

英文内容翻译规范

内容概览图生成规则

Obsidian 同步规范

索引

检索

二创 — 小红书内容生成

联动 — 公众号写作供料

分类规则

标签规范

写作素材交接（Skill Handoff）

命令速查

When it activates

SkillSafety

Source

Related skills

More in the registry