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ms-todo-sync · leoyeai | DecimalAI

Productivityby leoyeai

ms-todo-sync

A CLI skill to manage Microsoft To Do tasks via Microsoft Graph API. Supports listing, creating, completing, deleting, searching tasks and lists, viewing overdue/today/pending tasks, and exporting data.

Never made a case worse

SkillScore

SkillScore41/100

Test results 41

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

14%41%of test cases passed +27 pts

Without skill3 of 22

With skill9 of 22

6 fixed3 passed either way13 still failing0 broke

Measured on gemini-3.6-flash8/8/2026v19 comparable

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskShow all tasks in my 'Shopping' list using the CLI client, including completed items.

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-ms-todo-sync
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-ms-todo-sync")
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-ms-todo-sync

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-ms-todo-sync/SKILL.md https://app.decimal.ai/s/leoyeai-ms-todo-sync/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/leoyeai-ms-todo-sync/SKILL.md

This gets SKILL.md only. The skill's 1 other file is 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-ms-todo-sync

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-ms-todo-sync")
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-ms-todo-sync/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-ms-todo-sync/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 1 other file is 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-ms-todo-sync

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-ms-todo-sync")
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-ms-todo-sync/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/leoyeai-ms-todo-sync/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 1 other file is 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-ms-todo-sync

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-ms-todo-sync")
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-ms-todo-sync/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/leoyeai-ms-todo-sync/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 1 other file is 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-ms-todo-sync

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-ms-todo-sync")
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-ms-todo-sync/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/leoyeai-ms-todo-sync/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 1 other file is 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-ms-todo-sync

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-ms-todo-sync")
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-ms-todo-sync/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-ms-todo-sync/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 1 other file is 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-ms-todo-sync

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-ms-todo-sync")
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-ms-todo-sync/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/leoyeai-ms-todo-sync/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 1 other file is 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-ms-todo-sync

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-ms-todo-sync")
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-ms-todo-sync/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 1 other file is 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-ms-todo-sync

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-ms-todo-sync")
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-ms-todo-sync/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/leoyeai-ms-todo-sync/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 1 other file is 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-ms-todo-sync

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-ms-todo-sync")
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-ms-todo-sync/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/leoyeai-ms-todo-sync/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 1 other file is 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-ms-todo-sync

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-ms-todo-sync")
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-ms-todo-sync/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/leoyeai-ms-todo-sync/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 1 other file is 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-ms-todo-sync

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-ms-todo-sync")
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-ms-todo-sync/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/leoyeai-ms-todo-sync/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 1 other file is 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-ms-todo-sync

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-ms-todo-sync")
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-ms-todo-sync/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/leoyeai-ms-todo-sync/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 1 other file is 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-ms-todo-sync

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-ms-todo-sync/SKILL.md https://app.decimal.ai/s/leoyeai-ms-todo-sync/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/leoyeai-ms-todo-sync/SKILL.md

This gets SKILL.md only. The skill's 1 other file is 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-ms-todo-sync/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/leoyeai-ms-todo-sync.json

This gets SKILL.md only. The skill's 1 other file is 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

ms-todo-sync

A Microsoft To Do command-line client for managing tasks and lists via Microsoft Graph API.

Prerequisites

Python >= 3.9 must be installed.
uv (Python package manager) must be installed. Install via pip install uv or see https://docs.astral.sh/uv/.
Working directory: All commands MUST be run from the root of this skill (the directory containing this SKILL.md file).
Network access: Requires internet access to Microsoft Graph API endpoints.
Authentication: First-time use requires interactive login via browser. See Authentication section.
- Token cache: ~/.mstodo_token_cache.json (persists across sessions, auto-refreshed)
- Device flow cache: ~/.mstodo_device_flow.json (temporary)

Installation & Setup

First-Time Setup

Before using this skill for the first time, dependencies must be installed:

# Navigate to skill directory
cd <path-to-ms-todo-sync>

# Install dependencies using uv (recommended - creates isolated environment)
uv sync

# Alternative: Install dependencies with pip (uses global/active Python environment)
pip install -r requirements.txt

Dependencies:

Requires msal (Microsoft Authentication Library) and requests
Specified in requirements.txt
uv creates an isolated virtual environment to avoid conflicts

Environment Verification

After installation, verify the setup:

# Check if uv can find the script
uv run scripts/ms-todo-sync.py --help

# Expected: Command help text should be displayed

Troubleshooting:

If uv: command not found, install uv: pip install uv
If Python not found, install Python 3.9 or higher from https://python.org
If script fails with import errors, ensure dependencies are installed: uv sync or pip install -r requirements.txt

Security Notes

Uses official Microsoft Graph API via Microsoft's msal library
All code is plain Python (.py files), readable and auditable
Tokens stored locally in ~/.mstodo_token_cache.json
All API calls go directly to Microsoft endpoints

Command Reference

All commands follow this pattern:

uv run scripts/ms-todo-sync.py [GLOBAL_OPTIONS] <command> [COMMAND_OPTIONS]

Global Options

Option	Description
`-v, --verbose`	Show detailed information (IDs, dates, notes). Must be placed BEFORE the subcommand.
`--debug`	Enable debug mode to display API requests and responses. Useful for troubleshooting. Must be placed BEFORE the subcommand.

⚠️ Common mistake: Global options MUST come before the subcommand.

✅ uv run scripts/ms-todo-sync.py -v lists

✅ uv run scripts/ms-todo-sync.py --debug add "Task"

❌ uv run scripts/ms-todo-sync.py lists -v

Authentication

Authentication uses a two-step device code flow designed for non-interactive/agent environments.

`login get` — Get verification code

uv run scripts/ms-todo-sync.py login get

Output example:

✓ Verification code generated

Please visit the following link to log in:
https://microsoft.com/devicelogin

Enter verification code: ABC123XYZ

Verify with command: ms-todo-sync.py login verify

Agent behavior: Present the URL and verification code to the user. Wait for the user to confirm they have completed the browser login before proceeding.

`login verify` — Complete login

uv run scripts/ms-todo-sync.py login verify

Output on success:

✓ Authentication successful! Login information saved, you will be logged in automatically next time.

Output on failure:

✗ Authentication failed: <error description>

⚠️ This command blocks until Microsoft's server confirms the user completed browser authentication. Do NOT run this until the user confirms they have completed the browser step.

Exit code: 0 on success, 1 on failure.

`logout` — Clear saved login

uv run scripts/ms-todo-sync.py logout

Only use when the user explicitly asks to switch accounts or clear login data. Under normal circumstances, the token is cached and login is automatic.

List Management

`lists` — List all task lists

uv run scripts/ms-todo-sync.py lists
uv run scripts/ms-todo-sync.py -v lists  # with IDs and dates

Output example:

📋 Task Lists (3 total):

1. Tasks
2. Work
3. Shopping

`create-list` — Create a new list

uv run scripts/ms-todo-sync.py create-list "<name>"

Argument	Required	Description
`name`	Yes	Name of the new list

Output: ✓ List created: <name>

`delete-list` — Delete a list

uv run scripts/ms-todo-sync.py delete-list "<name>" [-y]

Argument/Option	Required	Description
`name`	Yes	Name of the list to delete
`-y, --yes`	No	Skip confirmation prompt

⚠️ This is a destructive operation. Without -y, the command will prompt for confirmation. Consider asking the user before deleting important lists.

Output: ✓ List deleted: <name>

Task Operations

`add` — Add a new task

uv run scripts/ms-todo-sync.py add "<title>" [options]

Option	Required	Default	Description
`title`	Yes	—	Task title (positional argument)
`-l, --list`	No	(default list)	Target list name. If not specified, uses your Microsoft To Do default list.
`-p, --priority`	No	`normal`	Priority: `low`, `normal`, `high`
`-d, --due`	No	—	Due date. Accepts days from now (`3` or `3d`) or date (`2026-02-15`). Note: Only date is supported, not time.
`-r, --reminder`	No	—	Reminder datetime. Formats: `3h` (hours), `2d` (days), `2026-02-15 14:30` (date+time with space, needs quotes), `2026-02-15T14:30:00` (ISO format), `2026-02-15` (date only, defaults to 09:00).
`-R, --recurrence`	No	—	Recurrence pattern. Formats: `daily` (every day), `weekdays` (Mon-Fri), `weekly` (every week), `monthly` (every month). With interval: `daily:2` (every 2 days), `weekly:3` (every 3 weeks), `monthly:2` (every 2 months). Note: Automatically sets start date.
`-D, --description`	No	—	Task description/notes
`-t, --tags`	No	—	Comma-separated tags (e.g., `"work,urgent"`)

Behavior: If the specified list doesn't exist, it will be automatically created.

Output example:

✓ List created: Work
✓ Task added: Complete report

`complete` — Mark a task as completed

uv run scripts/ms-todo-sync.py complete "<title>" [-l "<list>"]

Option	Required	Default	Description
`title`	Yes	—	Exact task title
`-l, --list`	No	(default list)	List name where the task resides. If not specified, uses your default list.

Output: ✓ Task completed: <title>

`delete` — Delete a task

uv run scripts/ms-todo-sync.py delete "<title>" [-l "<list>"] [-y]

Option	Required	Default	Description
`title`	Yes	—	Exact task title
`-l, --list`	No	(default list)	List name. If not specified, uses your default list.
`-y, --yes`	No	—	Skip confirmation prompt

⚠️ This is a destructive operation. Without -y, the command will prompt for confirmation. For routine cleanup or when user intent is clear, -y can be used to avoid blocking.

Output: ✓ Task deleted: <title>

Task Views

`tasks` — List tasks in a specific list

uv run scripts/ms-todo-sync.py tasks "<list>" [-a]

Option	Required	Default	Description
`list`	Yes	—	List name (positional argument)
`-a, --all`	No	—	Include completed tasks (default: only incomplete)

Output example:

📋 Tasks in list "Work" (2 total):

1. [In Progress] Write documentation ⭐
2. [In Progress] Review PR

`pending` — All incomplete tasks across all lists

uv run scripts/ms-todo-sync.py pending [-g]

Option	Required	Description
`-g, --group`	No	Group results by list

Output example (with -g):

📋 All incomplete tasks (3 total):

📂 Work:
  [In Progress] Write documentation ⭐
  [In Progress] Review PR

📂 Shopping:
  [In Progress] Buy groceries

`today` — Tasks due today

uv run scripts/ms-todo-sync.py today

Lists incomplete tasks with due date matching today. Output: 📅 No tasks due today if none found.

`overdue` — Overdue tasks

uv run scripts/ms-todo-sync.py overdue

Output example:

⚠️  Overdue tasks (1 total):

[In Progress] Submit report ⭐
   List: Work
   Overdue: 3 days

`detail` — View full task details

uv run scripts/ms-todo-sync.py detail "<title>" [-l "<list>"]

Option	Required	Default	Description
`title`	Yes	—	Task title (supports partial/fuzzy match)
`-l, --list`	No	(default list)	List name. If not specified, uses your default list.

When multiple tasks match, returns the most recently modified incomplete task. If all matches are completed, returns the most recently modified completed task.

`search` — Search tasks by keyword

uv run scripts/ms-todo-sync.py search "<keyword>"

Searches across all lists in both task titles and notes (case-insensitive).

Output example:

🔍 Search results (1 found):

[In Progress] Write documentation ⭐
   List: Work

`stats` — Task statistics

uv run scripts/ms-todo-sync.py stats

Output example:

📊 Task Statistics:

  Total lists: 3
  Total tasks: 15
  Completed: 10
  Pending: 5
  High priority: 2
  Overdue: 1

  Completion rate: 66.7%

`export` — Export all tasks to JSON

uv run scripts/ms-todo-sync.py export [-o "<filename>"]

Option	Required	Default	Description
`-o, --output`	No	`todo_export.json`	Output file path

Output: ✓ Tasks exported to: <filename>

Error Handling

Exit Codes

Code	Meaning
`0`	Success
`1`	Failure (not logged in, API error, invalid arguments, etc.)

Common Error Messages

Error	Cause	Resolution
`❌ Not logged in`	No cached token or token expired	Run `login get` then `login verify`
`ModuleNotFoundError: No module named 'msal'`	Dependencies not installed	Run `uv sync` or `pip install -r requirements.txt`
`❌ List not found: <name>`	Specified list does not exist	Check list name with `lists` command
`❌ Task not found: <name>`	No task with exact matching title	Check task title with `tasks` or `search`
`❌ Error: <message>`	API or network error	Retry; check network; use `--debug` for details

Agent Usage Guidelines

Critical Rules

Working directory: Always cd to the directory containing this SKILL.md before running commands.
Dependency installation: Before first use or when encountering import errors, run uv sync to ensure all dependencies are installed.
Task list organization: When adding tasks:
- First, run lists to see available task lists
- If user doesn't specify a list, tasks will be added to their default list (wellknownListName: "defaultList")
- Intelligently categorize tasks into appropriate lists (e.g., "Work", "Personal", "Shopping")
- If user mentions a context (work, home, shopping, etc.), use or create an appropriate list
- Lists will be auto-created if they don't exist, so feel free to use meaningful list names
Destructive operations: For delete and delete-list commands:
- These commands will prompt for confirmation by default (blocking behavior)
- Use -y flag to skip confirmation ONLY when:
  - User has explicitly requested to delete without confirmation
  - The deletion intent is unambiguous and confirmed through conversation
- When in doubt, ask the user for confirmation instead of using -y
Global option placement: -v and --debug must come BEFORE the subcommand, not after.
Do not retry login verify automatically: This command blocks waiting for user browser interaction. Only call it after the user confirms completion.
Check login status first: Before performing any task operations, run a lightweight command (e.g., lists) to verify authentication. Handle the "Not logged in" error gracefully.

Recommended Workflow for Agents

1. cd <skill_directory>
2. uv sync                                       # Ensure dependencies are installed (first time or after updates)
3. uv run scripts/ms-todo-sync.py lists          # Test auth & see available lists
   → If fails with exit code 1 ("Not logged in"):
     a. uv run scripts/ms-todo-sync.py login get  # Get code
     b. Present URL + code to user
     c. Wait for user confirmation
     d. uv run scripts/ms-todo-sync.py login verify
4. When adding tasks:
   → Analyze task context from user's description
   → Choose or create appropriate list name:
     - Work-related → "Work" list
     - Personal errands → "Personal" list  
     - Shopping items → "Shopping" list
     - Project-specific → Use project name as list
   → Add task with appropriate list via `-l` option
5. Verify results (e.g., list tasks after adding)

Example task categorization:

"Buy milk" → Shopping list (or default list if no context)
"Prepare report for meeting" → Work list
"Call dentist" → Personal list (or default list)
"Review PR for auth service" → Work or project-specific list

Note: If no list is specified, tasks are added to the user's default Microsoft To Do list.

Task Title Matching

complete and delete require exact title match.
detail and search support partial/fuzzy keyword match (case-insensitive).
When in doubt, use search first to find the exact title, then use it in subsequent commands.

Default List Behavior

When -l is not specified, the tool uses your Microsoft To Do default list (typically "Tasks"). To target a specific list, provide the -l option.

Quick Examples

# Check existing lists first
uv run scripts/ms-todo-sync.py lists

# Add task to specific list (list auto-created if needed)
uv run scripts/ms-todo-sync.py add "Report" -l "Work" -p high -d 3 -D "Q4 financials"

# Add task to default list (no -l option)
uv run scripts/ms-todo-sync.py add "Buy milk"

# Add task with reminder in 2 hours
uv run scripts/ms-todo-sync.py add "Call client" -r 2h

# Add task with specific reminder date and time
uv run scripts/ms-todo-sync.py add "Meeting" -d 2026-03-15 -r "2026-03-15 14:30"

# Add recurring tasks
uv run scripts/ms-todo-sync.py add "Daily standup" -l "Work" -R daily -d 7
uv run scripts/ms-todo-sync.py add "Weekly review" -R weekly -d 2026-02-17
uv run scripts/ms-todo-sync.py add "Gym" -R weekdays -l "Personal"  
uv run scripts/ms-todo-sync.py add "Monthly report" -R monthly -p high -d 30

# Search then complete (use exact title from search results)
uv run scripts/ms-todo-sync.py search "report"
uv run scripts/ms-todo-sync.py complete "Report" -l "Work"

# Delete (use -y only when user intent is clear)
uv run scripts/ms-todo-sync.py delete "Old task" -y

# Views
uv run scripts/ms-todo-sync.py -v pending -g          # all pending, grouped
uv run scripts/ms-todo-sync.py -v detail "report"      # task detail with fuzzy match
uv run scripts/ms-todo-sync.py export -o "backup.json"  # export all

About this skill

Automatic

Personal Assistant pack

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✓ 3 of 3 passed

Code scan15 of 15 checks clean

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

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IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

LeoYeAI / openclaw-master-skills

skills/ms-todo-sync/SKILL.md

View on GitHub ↗

License MITImported 8/2/2026Version v1Bundled 1 file · scripts

Illustrative Want to see what leoyeai/ms-todo-sync 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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ms-todo-sync

Prerequisites

Installation & Setup

First-Time Setup

Environment Verification

Security Notes

Command Reference

Global Options

Authentication

login get — Get verification code

login verify — Complete login

logout — Clear saved login

List Management

lists — List all task lists

create-list — Create a new list

delete-list — Delete a list

Task Operations

add — Add a new task

complete — Mark a task as completed

delete — Delete a task

Task Views

tasks — List tasks in a specific list

pending — All incomplete tasks across all lists

today — Tasks due today

overdue — Overdue tasks

detail — View full task details

search — Search tasks by keyword

stats — Task statistics

export — Export all tasks to JSON

Error Handling

Exit Codes

Common Error Messages

Agent Usage Guidelines

Critical Rules

Recommended Workflow for Agents

Task Title Matching

Default List Behavior

Quick Examples

SkillSafety

Source

Related skills

More in the registry

`login get` — Get verification code

`login verify` — Complete login

`logout` — Clear saved login

`lists` — List all task lists

`create-list` — Create a new list

`delete-list` — Delete a list

`add` — Add a new task

`complete` — Mark a task as completed

`delete` — Delete a task

`tasks` — List tasks in a specific list

`pending` — All incomplete tasks across all lists

`today` — Tasks due today

`overdue` — Overdue tasks

`detail` — View full task details

`search` — Search tasks by keyword

`stats` — Task statistics

`export` — Export all tasks to JSON