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Anki Card Creator · leoyeai | DecimalAI

Documentationby leoyeai

Anki Card Creator

Convert medical textbook content, lecture notes, and study materials into Anki flashcards using spaced repetition optimization. Supports multiple card types (basic, cloze, image occlusion) with automated tagging and deck organization for efficient medical exam preparation.

Never made a case worse

SkillScore

SkillScore95/100

Test results 95

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

45%95%of test cases passed +50 pts

Without skill10 of 22

With skill21 of 22

11 fixed10 passed either way1 still failing0 broke

Measured on gemini-3.6-flash8/6/2026v1

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskProvide a terminal command using `scripts/main.py` to generate an anatomical structure card for 'Coronary arteries'. Specify its location as 'Surface of heart' and its function as 'Supply blood to myocardium', outputting to `coronary.txt`.

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-anki-card-creator
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-anki-card-creator")
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-anki-card-creator

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-anki-card-creator/SKILL.md https://app.decimal.ai/s/leoyeai-anki-card-creator/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/leoyeai-anki-card-creator/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-anki-card-creator

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-anki-card-creator")
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-anki-card-creator/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-anki-card-creator/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-anki-card-creator

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-anki-card-creator")
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-anki-card-creator/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/leoyeai-anki-card-creator/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-anki-card-creator

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-anki-card-creator")
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-anki-card-creator/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/leoyeai-anki-card-creator/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-anki-card-creator

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-anki-card-creator")
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-anki-card-creator/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/leoyeai-anki-card-creator/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-anki-card-creator

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-anki-card-creator")
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-anki-card-creator/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-anki-card-creator/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-anki-card-creator

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-anki-card-creator")
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-anki-card-creator/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/leoyeai-anki-card-creator/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-anki-card-creator

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-anki-card-creator")
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-anki-card-creator/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-anki-card-creator

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-anki-card-creator")
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-anki-card-creator/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/leoyeai-anki-card-creator/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-anki-card-creator

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-anki-card-creator")
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-anki-card-creator/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/leoyeai-anki-card-creator/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-anki-card-creator

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-anki-card-creator")
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-anki-card-creator/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/leoyeai-anki-card-creator/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-anki-card-creator

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-anki-card-creator")
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-anki-card-creator/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/leoyeai-anki-card-creator/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-anki-card-creator

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-anki-card-creator")
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-anki-card-creator/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/leoyeai-anki-card-creator/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-anki-card-creator

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-anki-card-creator/SKILL.md https://app.decimal.ai/s/leoyeai-anki-card-creator/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/leoyeai-anki-card-creator/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-anki-card-creator/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/leoyeai-anki-card-creator.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 8/6/2026
Source: LeoYeAI/openclaw-master-skills ↗
License: MIT

Manage it in DecimalAI

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Use this skill

SKILL.md

Anki Card Creator

Overview

Intelligent flashcard generation tool that transforms medical study materials into Anki-compatible cards optimized for long-term retention through evidence-based spaced repetition.

Key Capabilities:

Multi-Format Input: PDF textbooks, lecture slides, notes, web articles
Card Type Selection: Basic, reversible, cloze deletion, image occlusion
Spaced Repetition Optimization: Cards formatted for optimal review intervals
Automated Tagging: Hierarchical organization by subject and topic
Media Integration: Auto-download and embed relevant images
Batch Processing: Convert entire chapters or courses efficiently

When to Use

✅ Use this skill when:

Preparing for medical board exams (USMLE, MCAT, specialty boards)
Memorizing drug names, mechanisms, and side effects
Learning anatomy structures and relationships
Retaining biochemical pathways and reactions
Creating pathology differential diagnosis cards
Converting lecture notes to active recall format
Building comprehensive review decks from textbooks

❌ Do NOT use when:

Learning conceptual understanding → Use textbooks/videos first
Memorizing without context → Ensure comprehension before card creation
Creating cards for rapidly changing information → Use current resources
Substituting clinical experience → Cards supplement, not replace practice
Complex procedural skills → Use simulation or hands-on training

Integration:

Upstream: abstract-summarizer (textbook chapter condensation), pdf-text-extractor (content extraction)
Downstream: anki-sync-server (cloud backup), study-schedule-optimizer (review planning)

Core Capabilities

1. Cloze Deletion Generation

Create fill-in-the-blank cards from dense text:

from scripts.card_creator import AnkiCardCreator

creator = AnkiCardCreator()

# Generate cloze cards from text
text = """
Acute inflammation is characterized by five cardinal signs: 
redness (rubor), heat (calor), swelling (tumor), pain (dolor), 
and loss of function (functio laesa). These result from 
vasodilation, increased vascular permeability, and leukocyte 
infiltration.
"""

cards = creator.create_cloze_cards(
    text=text,
    n_cards=3,  # Generate 3 cards from this text
    difficulty="intermediate",
    tags=["Pathology", "Inflammation", "General_Pathology"]
)

# Output format (Anki-compatible)
# Card 1: "Acute inflammation is characterized by {{c1::five}} cardinal signs..."
# Card 2: "...signs: {{c1::redness}} (rubor), {{c2::heat}} (calor)..."

Cloze Strategies:

Strategy	Use Case	Example
Single Deletion	Key facts	"The {{c1::liver}} is the largest internal organ"
Multiple Deletions	Lists/groups	"CRAB symptoms: {{c1::Calcium}}, {{c2::Renal}}, {{c3::Anemia}}, {{c4::Bone}}"
Hierarchical	Progressive detail	"{{c1::Metformin}} is a {{c2::biguanide}} that {{c3::decreases hepatic glucose production}}"

2. Basic and Reversible Cards

Generate question-answer pairs:

# Create basic cards
cards = creator.create_basic_cards(
    content={
        "What is the mechanism of action of penicillin?": 
            "Inhibition of bacterial cell wall synthesis by binding to PBPs",
        "What are the major side effects of ACE inhibitors?":
            "Dry cough, hyperkalemia, angioedema, hypotension"
    },
    reversible=True,  # Create reverse cards too
    tags=["Pharmacology", "Antibiotics"]
)

Card Types:

Basic: Question → Answer
Reversible: Both directions (Q→A and A→Q)
Type-in: Student types answer for active recall
Hint Cards: Progressive disclosure with hints

3. Image Occlusion Cards

Create visual learning cards from diagrams:

# Image occlusion for anatomy
cards = creator.create_image_occlusion(
    image_path="brachial_plexus.png",
    occlude_regions=[
        {"label": "Musculocutaneous nerve", "coords": (120, 200, 200, 240)},
        {"label": "Median nerve", "coords": (300, 250, 380, 290)},
        {"label": "Ulnar nerve", "coords": (400, 280, 480, 320)}
    ],
    card_type="one_by_one"  # or "all_at_once"
)

Occlusion Types:

One by One: Reveal structures progressively
All at Once: Identify all occluded regions
Transparent: Hint visible through occlusion
Colored: Different colors for different structures

4. Smart Tagging and Organization

Automatically organize cards into logical hierarchies:

# Auto-tag based on content
cards = creator.process_textbook_chapter(
    chapter_text=pathoma_chapter,
    source="Pathoma - Hematopoiesis",
    auto_tag=True,
    tag_hierarchy=[
        "Pathoma",
        "{{chapter_name}}",
        "{{section_name}}"
    ]
)

# Results in tags like:
# Pathoma::Hematopoiesis::Red_Cell_Disorders
# Pathoma::Hematopoiesis::White_Cell_Disorders

Tagging Strategies:

Source-based: First Aid, Pathoma, Sketchy
Subject-based: Anatomy, Physiology, Pharmacology
Exam-based: USMLE_Step1, Step2_CK, Shelf_Exams
Difficulty: High_Yield, Medium_Yield, Low_Yield

Common Patterns

Pattern 1: Textbook Chapter Conversion

Scenario: Convert entire First Aid chapter to Anki deck.

# Extract and convert chapter
python scripts/main.py \
  --input first_aid_cardiology.pdf \
  --chapter "Ischemic Heart Disease" \
  --card-type cloze \
  --n-cards-per-page 3 \
  --tags "First_Aid::Cardiology::IHD" \
  --output ischemic_heart_disease.apkg

# Import directly to Anki
# File ready for import with media included

Workflow:

Read chapter for understanding first
Run conversion tool
Review generated cards for accuracy
Import to Anki
Study with standard spaced repetition

Pattern 2: Drug Cards with Images

Scenario: Create comprehensive pharmacology cards.

# Generate drug cards with mechanisms
drugs = [
    {
        "name": "Metformin",
        "class": "Biguanide",
        "mechanism": "Activates AMPK, decreases hepatic gluconeogenesis",
        "indications": "Type 2 diabetes, PCOS",
        "side_effects": "GI upset, lactic acidosis (rare), B12 deficiency",
        "image": "metformin_structure.png"
    }
]

cards = creator.create_drug_cards(
    drugs=drugs,
    include_structures=True,
    include_mechanism_diagrams=True,
    tags=["Pharmacology", "Diabetes", "First_Line"]
)

Card Format:

Front: Metformin - Class?
Back: Biguanide
Tags: Pharmacology::Diabetes::First_Line

Front: Metformin - Mechanism?
Back: Activates AMPK → decreases hepatic gluconeogenesis
Image: [mechanism diagram]
Tags: Pharmacology::Diabetes::Mechanism

Front: Metformin - Side effects?
Back: GI upset, lactic acidosis (rare), B12 deficiency
Tags: Pharmacology::Diabetes::Side_Effects

Pattern 3: Pathology Differential Cards

Scenario: Create cards for differential diagnosis practice.

# Differential diagnosis cards
cards = creator.create_differential_cards(
    condition="Cough with hemoptysis",
    differentials=[
        {"diagnosis": "Lung cancer", "key_features": "Smoker, weight loss, mass on CT"},
        {"diagnosis": "TB", "key_features": "Immigrant, night sweats, cavitary lesion"},
        {"diagnosis": "PE", "key_features": "Sudden onset, tachypnea, D-dimer elevated"},
        {"diagnosis": "Bronchiectasis", "key_features": "Chronic cough, purulent sputum, dilated airways"}
    ],
    card_type="compare_contrast"
)

Card Types:

Feature → Diagnosis: "Smoker + hemoptysis + weight loss → ?"
Diagnosis → Features: "Lung cancer presentation?"
Compare: "Differentiate lung cancer vs TB"

Pattern 4: Lecture Notes to Cards

Scenario: Convert professor's lecture slides to study cards.

# Process lecture PDF
python scripts/main.py \
  --input lecture_slides.pdf \
  --source "Dr_Smith_Cardiology_Lecture_5" \
  --card-type mixed \
  --extract-images \
  --auto-tag \
  --output cardiology_lecture_5.apkg

# Review and edit in Anki
# Delete low-yield cards
# Add personal mnemonics

Post-Processing Tips:

Delete obvious or overly simple cards
Merge redundant cards
Add personal memory hooks
Suspend low-yield topics

Complete Workflow Example

Building comprehensive USMLE Step 1 deck:

# Step 1: Process multiple sources
python scripts/main.py \
  --input first_aid_pathology.pdf \
  --source "First_Aid_2024" \
  --card-type cloze \
  --tags "First_Aid::Pathology" \
  --output fa_pathology.apkg

python scripts/main.py \
  --input sketchy_pharm.pdf \
  --source "Sketchy_Pharm" \
  --card-type basic \
  --include-images \
  --tags "Sketchy::Pharm" \
  --output sketchy_pharm.apkg

# Step 2: Merge decks
python scripts/main.py \
  --merge fa_pathology.apkg sketchy_pharm.apkg \
  --output usmle_step1_master.apkg

# Step 3: Add leech tags for difficult cards
python scripts/main.py \
  --input usmle_step1_master.apkg \
  --tag-leeches \
  --leech-threshold 8 \
  --output usmle_step1_tagged.apkg

Python API:

from scripts.card_creator import AnkiCardCreator
from scripts.importers import PDFImporter

# Initialize
creator = AnkiCardCreator()
importer = PDFImporter()

# Import and process textbook
content = importer.import_pdf(
    path="robbins_pathologic_basis_of_disease.pdf",
    pages="150-200",  # Inflammation chapter
    extract_images=True
)

# Create cloze cards
cards = creator.create_cloze_cards(
    text=content.text,
    images=content.images,
    n_cards=50,
    difficulty="advanced",
    tags=["Robbins", "General_Pathology", "Inflammation"]
)

# Add image occlusion for diagrams
for diagram in content.diagrams:
    occlusion_cards = creator.create_image_occlusion(
        image=diagram,
        auto_detect_labels=True
    )
    cards.extend(occlusion_cards)

# Export Anki package
creator.export_apkg(
    cards=cards,
    deck_name="Robbins_Inflammation",
    output_path="robbins_inflammation.apkg"
)

print(f"Created {len(cards)} cards ready for Anki import")

Quality Checklist

Card Quality:

One fact per card (atomicity)
Clear, unambiguous questions
Answers specific and complete
Cloze deletions don't give away answer
Images high resolution and relevant
Tags hierarchical and consistent

Educational Value:

Cards test high-yield information
Difficulty appropriate for level
Connections between related concepts
Clinical context included where relevant
No duplicate or near-duplicate cards

Technical Quality:

Valid Anki format (import tested)
Media files properly linked
UTF-8 encoding for special characters
CSS styling readable on mobile
Card types appropriate for content

Before Study:

CRITICAL: Review cards for accuracy
CRITICAL: Delete cards for mastered material
Personalize with own mnemonics
Adjust card order if needed
Set appropriate daily review limits

Common Pitfalls

Content Issues:

❌ Too much information → "Cramming" cards with multiple facts
- ✅ One concept per card; break complex topics into multiple cards
❌ Memorization without understanding → Memorizing without context
- ✅ Include "why" and clinical significance
❌ Outdated information → Old guidelines or disproven theories
- ✅ Verify against current textbooks and guidelines

Card Design Issues:

❌ Ambiguous clozes → "The {{c1::liver}} produces {{c2::bile}}" (which one is being asked?)
- ✅ Clear question: "The liver produces ?" or "What organ produces bile?"
❌ Overlapping cards → Testing same fact multiple ways
- ✅ Merge redundant cards; each fact tested once optimally
❌ Recognition vs. recall → Cards too easy (recognition only)
- ✅ Use cloze deletions and type-in cards for active recall

Study Strategy Issues:

❌ Too many new cards → 100+ new cards/day leads to burnout
- ✅ Sustainable pace: 20-30 new cards/day
❌ No review of missed cards → Ignoring leeches
- ✅ Tag and review difficult cards separately
❌ Passive card creation → Making cards without studying
- ✅ Create cards for immediate use; don't build massive backlog

References

Available in references/ directory:

anki_format_spec.md - Anki .apkg file format specifications
spaced_repetition_principles.md - Evidence-based SRS guidelines
card_design_best_practices.md - Effective flashcard design
usmle_high_yield_facts.md - High-yield content for boards
image_sources.md - Open-access medical images
tagging_conventions.md - Standardized tag hierarchies

Scripts

Located in scripts/ directory:

main.py - CLI interface for card creation
card_creator.py - Core card generation engine
cloze_generator.py - Cloze deletion algorithms
image_occlusion.py - Visual card creation
pdf_importer.py - Textbook and slide import
tag_manager.py - Automated tagging system
media_handler.py - Image download and optimization
anki_exporter.py - .apkg file generation

Limitations

Context Dependency: May miss nuanced explanations without full context
Image Licensing: Must verify copyright for extracted images
Complex Diagrams: Simple occlusion may not capture complex relationships
Personalization: Generic cards lack personal memory hooks
Volume Control: Easy to create too many cards; requires curation
Active Learning: Cards supplement but don't replace active problem-solving

Parameters

Parameter	Type	Default	Required	Description
`--input`, `-i`	string	-	No	Input text file with Q&A pairs
`--output`, `-o`	string	anki_cards.txt	No	Output file (Anki TSV format)
`--drug`	flag	-	No	Create drug information card
`--anatomy`	flag	-	No	Create anatomy card
`--name`	string	-	No	Drug or structure name
`--mechanism`	string	-	No	Mechanism of action (for drug cards)
`--indications`	string	-	No	Clinical indications (for drug cards)
`--side-effects`	string	-	No	Side effects (for drug cards)
`--location`	string	-	No	Anatomical location (for anatomy cards)
`--function`	string	-	No	Function (for anatomy cards)

Usage

Basic Usage

# Create drug card
python scripts/main.py --drug --name "Metformin" --mechanism "Decreases hepatic glucose production" --indications "Type 2 diabetes" --output metformin.txt

# Create anatomy card
python scripts/main.py --anatomy --name "Coronary arteries" --location "Surface of heart" --function "Supply oxygenated blood to myocardium" --output coronary.txt

# Parse Q&A file
python scripts/main.py --input questions.txt --output deck.txt

Input File Format

Q: What is the mechanism of action of Metformin?
A: Decreases hepatic glucose production, increases insulin sensitivity

Q: Which artery supplies the left ventricle?
A: Left anterior descending artery (LAD)

Risk Assessment

Risk Indicator	Assessment	Level
Code Execution	Python script executed locally	Low
Network Access	No external API calls	Low
File System Access	Read input file, write to output file	Low
Instruction Tampering	Standard prompt guidelines	Low
Data Exposure	Output saved only to specified location	Low

Security Checklist

No hardcoded credentials or API keys
No unauthorized file system access
Output does not expose sensitive information
Prompt injection protections in place
Input validation for file paths
Output directory restricted to workspace
Script execution in sandboxed environment

Prerequisites

# Python 3.7+
# No additional packages required (uses standard library)

Evaluation Criteria

Success Metrics

Successfully creates Anki-compatible TSV files
Supports drug and anatomy card types
Parses Q&A files correctly
Generates valid HTML formatting

Test Cases

Drug Card: Create Metformin card → Valid TSV output with formatted front/back
Anatomy Card: Create coronary artery card → Valid TSV with location and function
File Parse: Parse Q&A text file → Multiple cards generated

Lifecycle Status

Current Stage: Draft
Next Review Date: 2026-03-06
Known Issues: None
Planned Improvements:
- Add Cloze deletion support
- Support image inclusion
- Add .apkg export format

🧠 Study Tip: The best flashcard is one you'll actually review. Create cards for material you genuinely need to memorize, and keep the daily review load sustainable. Quality over quantity—better to deeply learn 1000 cards than superficially memorize 5000.

About this skill

Automatic

Tutoring & Education 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/anki-card-creator/SKILL.md

View on GitHub ↗

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

Illustrative Want to see what leoyeai/anki-card-creator 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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Anki Card Creator

Overview

When to Use

Core Capabilities

1. Cloze Deletion Generation

2. Basic and Reversible Cards

3. Image Occlusion Cards

4. Smart Tagging and Organization

Common Patterns

Pattern 1: Textbook Chapter Conversion

Pattern 2: Drug Cards with Images

Pattern 3: Pathology Differential Cards

Pattern 4: Lecture Notes to Cards

Complete Workflow Example

Quality Checklist

Common Pitfalls

References

Scripts

Limitations

Parameters

Usage

Basic Usage

Input File Format

Risk Assessment

Security Checklist

Prerequisites

Evaluation Criteria

Success Metrics

Test Cases

Lifecycle Status

SkillSafety

Source

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