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Slide Creator · LeoYeAI | DecimalAI

Design & Mediaby LeoYeAI

Slide Creator

Create beautiful, zero-dependency HTML presentations that run entirely in the browser — no npm, no build tools. 21 curated style presets with named layout variations, visual style discovery with live previews, viewport-fitted slides, inline browser editing, Presenter Mode, and optional PPTX export. Content-type routing suggests the best style for pitch decks, dev docs, data reports, and more. Supports --plan (outline), --generate (HTML from plan), and --export pptx flags.

SkillScore

SkillScore45/100

Test results 45

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

14%45%of test cases passed +32 pts

Without skill3 of 22

With skill10 of 22

7 fixed3 passed either way12 still failing0 broke

Measured on gemini-3.6-flash7/27/2026v118 comparable

Track record

Agent runs: 0; All time

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 slide-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("slide-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 slide-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/slide-creator/SKILL.md https://app.decimal.ai/s/slide-creator/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/slide-creator/SKILL.md

This gets SKILL.md only. The skill's 15 other files are not included.

Other ways to add it

Claude Code docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"
decimalai skills add slide-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("slide-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/slide-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/slide-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 15 other files are not included.

Other ways to add it

Claude Agent SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai-agents]"
decimalai skills add slide-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("slide-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/slide-creator/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/slide-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 15 other files are not included.

Other ways to add it

OpenAI Agents docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai]"
decimalai skills add slide-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("slide-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/slide-creator/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/slide-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 15 other files are not included.

Other ways to add it

OpenAI SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[anthropic]"
decimalai skills add slide-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("slide-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/slide-creator/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/slide-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 15 other files are not included.

Other ways to add it

Anthropic docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[google-genai]"
decimalai skills add slide-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("slide-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/slide-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/slide-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 15 other files are not included.

Other ways to add it

Gemini API docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[langchain]" langchain-openai
decimalai skills add slide-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("slide-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/slide-creator/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/slide-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 15 other files are not included.

Other ways to add it

LangChain docs

CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"
decimalai skills add slide-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("slide-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/slide-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 15 other files are not included.

Other ways to add it

CrewAI docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[adk]"
decimalai skills add slide-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("slide-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/slide-creator/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/slide-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 15 other files are not included.

Other ways to add it

Google ADK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[pydantic-ai]"
decimalai skills add slide-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("slide-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/slide-creator/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/slide-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 15 other files are not included.

Other ways to add it

Pydantic AI docs

Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents
decimalai skills add slide-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("slide-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/slide-creator/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/slide-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 15 other files are not included.

Other ways to add it

Deep Agents docs

Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework
decimalai skills add slide-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("slide-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/slide-creator/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/slide-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 15 other files are not included.

Other ways to add it

Microsoft Agent Framework docs

Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents
decimalai skills add slide-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("slide-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/slide-creator/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/slide-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 15 other files are not included.

Other ways to add it

Strands docs

Adds every file the skill has, pinned so you can update it. Cursor, Copilot, Cline and Warp read this folder by themselves.

pip install "decimalai>=0.15"
decimalai skills add slide-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/slide-creator/SKILL.md https://app.decimal.ai/s/slide-creator/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/slide-creator/SKILL.md

This gets SKILL.md only. The skill's 15 other files are not included.

Other ways to add it

Cursor and other editors docs

Fetch the file and give its text to your model as instructions. No account or package needed.

Get the file

curl -fsSL https://app.decimal.ai/s/slide-creator/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/slide-creator.json

This gets SKILL.md only. The skill's 15 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 7/27/2026
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

Slide Creator

Generate zero-dependency HTML presentations that run entirely in the browser. This skill guides users from raw ideas to a polished, animated slide deck — using visual style discovery ("show, don't tell") to nail the aesthetic before writing a line of code.

Core Philosophy

Zero Dependencies — Single HTML files with inline CSS/JS. No npm, no build tools.
Show, Don't Tell — People can't articulate design preferences until they see options. Generate visual previews rather than asking abstract questions like "do you want minimalist or bold?"
Distinctive Design — Avoid generic AI aesthetics (Inter font, purple gradients, predictable heroes). Every deck should feel custom-crafted.
Viewport Fitting — Slides must fit exactly in the viewport with no scrolling. Content that overflows gets split across slides, not squished. A presentation that scrolls mid-slide is broken — this is why we enforce density limits.
Plan Before Generate — For complex decks, --plan creates a PLANNING.md outline first; --generate then produces HTML. Separating thinking from execution leads to better structure and less backtracking.

Command Flags

Parse the invocation to determine mode:

--plan [prompt] — Planning mode. Inspect resources/, analyze the prompt, create PLANNING.md. Stop — do NOT generate HTML.
--generate [instructions] — Generation mode. Read PLANNING.md if present (skip Phase 1/2 questions), then generate HTML.
--export pptx [--scale N] — Export the most recently modified HTML as PPTX via the bundled Python script. Requires Python 3 + pip install playwright python-pptx. No Node.js required.
No flag — Auto-detect mode (Phase 0).

Planning Mode (`--plan`)

Scan resources/ — read text/markdown files, note images. Tell the user what was found (or "Planning from prompt only" if empty).
Extract: topic, audience, tone, language, slide count, goals from the prompt.
Draft the plan following references/planning-template.md.
Save as PLANNING.md in the working directory.
Present slide count, structure, and key decisions. Ask for approval.
Stop. Do NOT generate HTML.

Export Mode (`--export pptx`)

Find *.html in current directory (prefer most recently modified).
Run: python3 <skill-path>/scripts/export-pptx.py <presentation.html> [output.pptx]
Report the PPTX file path and slide count.

The script uses Playwright with the user's existing system Chrome (--channel chrome flag, no Chromium download). It captures pixel-perfect screenshots of each slide and assembles them into a PPTX. Only pip install playwright python-pptx required — no Node.js, no 300MB browser download. If system Chrome is not found, the script will report an error and ask the user to install Chrome.

Phase 0: Detect Mode

Determine what the user wants:

Mode A — New Presentation: Check for PLANNING.md first. If it exists, read it as source of truth and jump directly to Phase 3 — skip Phase 1/2.
Mode B — PPT Conversion: User has a .ppt/.pptx file → go to Phase 4.
Mode C — Enhance Existing: Read the existing HTML, understand its structure, then enhance. When adding content, always check viewport fit — if adding would overflow a slide, split the content rather than cramming it in. Proactively split and inform the user.

Content-type → Style hints (use when user hasn't chosen a style):

Content type	Suggested styles
Data report / KPI dashboard	Data Story, Enterprise Dark, Swiss Modern
Business pitch / VC deck	Bold Signal, Aurora Mesh, Enterprise Dark
Developer tool / API docs	Terminal Green, Neon Cyber, Neo-Retro Dev Deck
Research / thought leadership	Modern Newspaper, Paper & Ink, Swiss Modern
Creative / personal brand	Vintage Editorial, Split Pastel, Neo-Brutalism
Product launch / SaaS	Aurora Mesh, Glassmorphism, Electric Studio
Education / tutorial	Notebook Tabs, Paper & Ink, Pastel Geometry
Chinese content	Chinese Chan, Aurora Mesh, Blue Sky
Hackathon / indie dev	Neo-Retro Dev Deck, Neo-Brutalism, Terminal Green

Phase 1: Content Discovery

First, silently scan for a resources/ folder. If found, read text/markdown files and note images as background context. Don't ask the user to take any action.

Then gather everything in a single AskUserQuestion call with all 5 questions at once — collecting everything before submitting avoids back-and-forth.

Purpose (single select): Pitch deck / Teaching+Tutorial / Conference talk / Internal presentation
Length (single select): Short 5-10 / Medium 10-20 / Long 20+
Content (single select): All content ready / Rough notes / Topic only
Images (single select): No images / ./assets / Other (user types path)
Inline Editing (single select): Yes — edit text in-browser, auto-save (Recommended) / No — presentation only

Default: Always include inline editing unless user explicitly selects "No". When --generate skips Phase 1, include inline editing by default.

If user has content, ask them to share it after submitting the form.

Language: Detect from the user's message — never default to a fixed language. Maintain the detected language throughout all slide text including labels, CTAs, and captions. English may appear as secondary annotation text only when the style calls for it.

Image Evaluation

Skip if user chose "No images." Text-only decks are fully first-class — CSS-generated gradients, shapes, and typography create compelling visuals without any images.

If images are provided:

ls the folder, then use Read (multimodal) to view each image.
For each image: mark USABLE or NOT USABLE (with reason: blurry, irrelevant, broken) + what it represents + dominant colors + shape.
Build a slide outline that co-designs text and images from the start. This is not "plan slides, then fit images in after." Example: 3 usable product screenshots → 3 feature slides anchored by those screenshots.
Present the evaluation and proposed outline, then confirm via AskUserQuestion (Looks good → Style B / Adjust images / Adjust outline).

Phase 2: Style Discovery

Most people can't articulate design preferences in words. Generate 3 mini visual previews and let them react — this is the "wow moment" of the skill.

Style Path

Ask via AskUserQuestion:

"Show me options" → ask mood question → generate 3 previews based on answer
"I know what I want" → show preset picker (Bold Signal / Blue Sky / Modern Newspaper / Neo-Retro Dev Deck — with "Other" option for all 21 presets)

Before showing presets, silently scan <skill-path>/themes/ for subdirectories. Skip any directory whose name starts with _ (those are examples/templates, not real themes). Each remaining subdirectory with a reference.md is a custom theme. Append them to the preset list as Custom: <folder-name> entries. If any custom themes exist, mention them first: "I also found N custom theme(s) in your themes/ folder."

Available Presets (full details in STYLE-DESC.md):

Preset	Vibe	Best For
Bold Signal	Confident, high-impact	Pitch decks, keynotes
Electric Studio	Clean, professional	Agency presentations
Creative Voltage	Energetic, retro-modern	Creative pitches
Dark Botanical	Elegant, sophisticated	Premium brands
Blue Sky	Clean, airy, enterprise-ready	SaaS pitches, AI/tech decks
Notebook Tabs	Editorial, organized	Reports, reviews
Pastel Geometry	Friendly, approachable	Product overviews
Split Pastel	Playful, modern	Creative agencies
Vintage Editorial	Witty, personality-driven	Personal brands
Neon Cyber	Futuristic, techy	Tech startups
Terminal Green	Developer-focused	Dev tools, APIs
Swiss Modern	Minimal, precise	Corporate, data
Paper & Ink	Literary, thoughtful	Storytelling
Aurora Mesh	Vibrant, premium SaaS	Product launches, VC pitch
Enterprise Dark	Authoritative, data-driven	B2B, investor decks, strategy
Glassmorphism	Light, translucent, modern	Consumer tech, brand launches
Neo-Brutalism	Bold, uncompromising	Indie dev, creative manifesto
Chinese Chan	Still, contemplative	Design philosophy, brand, culture
Data Story	Clear, precise, persuasive	Business review, KPI, analytics
Modern Newspaper	Punchy, authoritative, editorial	Business reports, thought leadership, research summaries
Neo-Retro Dev Deck	Opinionated, technical, handmade	Dev tool launches, API docs, hackathon presentations

Mood → Preset mapping:

Mood	Style Options
Impressed/Confident	Bold Signal, Enterprise Dark, Neo-Brutalism
Excited/Energized	Creative Voltage, Neon Cyber, Aurora Mesh
Calm/Focused	Notebook Tabs, Paper & Ink, Chinese Chan
Inspired/Moved	Dark Botanical, Vintage Editorial, Glassmorphism
Clean/Enterprise	Blue Sky, Electric Studio, Enterprise Dark
Data-Driven	Data Story, Enterprise Dark, Swiss Modern
Playful/Creative	Split Pastel, Pastel Geometry, Neo-Brutalism
Developer-Focused	Terminal Green, Neon Cyber, Neo-Retro Dev Deck
Editorial/Organized	Notebook Tabs, Vintage Editorial, Modern Newspaper

Generate Previews

Create 3 mini HTML files in .claude-design/slide-previews/ (style-a/b/c.html). Each is a single title slide (~50-100 lines, self-contained) demonstrating typography, color palette, and animation style.

If a USABLE logo was found in Step 1.2, embed it (base64) into each preview — seeing their own brand in 3 different aesthetics makes the choice feel personal, not abstract.

Never use: Inter/Roboto/Arial as display fonts, generic purple-on-white gradients, predictable centered hero layouts.

Present the 3 files with a one-sentence description each, then ask via AskUserQuestion which they prefer (Style A / B / C / Mix elements).

Phase 3: Generate Presentation

Generate the presentation based on content from Phase 1 and style from Phase 2. If PLANNING.md exists, it's the source of truth — skip Phases 1 and 2.

If Blue Sky style is selected → use the starter template

Read references/blue-sky-starter.html and use it as the base.

All 10 signature visual elements (orbs, noise texture, grid, glassmorphism, spring-physics horizontal track, gradient text, cloud hero, pill dots, counter, entrance animation) are already implemented in that file. You only need to:

Set --slide-count in :root to your actual slide count
Replace the example slides in #track with your content, following the slide-type patterns in the comment block
Fill the orbPositions array in JS — one [l1,t1,s1, l2,t2,s2, l3,t3,s3] entry per slide

Do not rewrite the visual system CSS. Do not change the track/slide layout. Content goes inside .slide wrappers using the pre-built component classes: .g (glass card), .gt (gradient text), .pill, .stat, .divider, .cols2/3/4, .ctable, .co (amber callout), .warn (red warning), .info (blue info), .layer (org row), ul.bl (bullet list).

If a custom theme from themes/ is selected

Read the theme's reference.md for style constraints. If a starter.html exists in the theme folder, use it as the base (same as Blue Sky). Otherwise, follow the standard references below and apply the custom theme's colors, typography, and layout rules.

For all other styles → read the standard references

Read references/html-template.md — it contains the required HTML structure, JavaScript patterns, animation recipes, and edit button implementation.

IMPORTANT — MUST READ before writing any HTML. Do NOT implement the edit button or presenter button from memory. The correct pattern uses a hotzone <div> + JS mouseenter/mouseleave with a 400ms grace period. Using body:hover is a known mistake — it makes the button permanently visible. The exact implementation is in html-template.md; copy it directly.

Also read STYLE-DESC.md for viewport fitting CSS, responsive breakpoints, style preset details, and CSS gotchas (especially: never negate CSS functions directly — use calc(-1 * clamp(...)) not -clamp(...)).

Viewport Fitting

Each slide must equal exactly one viewport height (100vh / 100dvh). When content doesn't fit, split it across slides — never allow scrolling within a slide. This is what separates a polished presentation from a broken one.

Content density limits:

Slide Type	Maximum
Title slide	1 heading + 1 subtitle
Content slide	1 heading + 4-6 bullets
Feature grid	1 heading + 6 cards max (2×3 or 3×2)
Code slide	1 heading + 8-10 lines
Quote slide	1 quote (3 lines max) + attribution
Image slide	1 heading + 1 image (max 60vh height)

When in doubt → split the slide.

Visual Rhythm: Alternate between text-heavy and visual-heavy slides. Three or more consecutive slides with the same layout signal low effort. Vary between: headline-dominant → data/diagram → evidence list → quote or visual break → headline-dominant. Every 4–5 slides, one slide should be nearly empty (a single statement, a big number, or a quote).

Diagram Slides (when content calls for a visual relationship)

When a slide needs to show a process, comparison, hierarchy, timeline, or data — generate an inline SVG diagram instead of bullet points.

Read references/diagram-patterns.md for ready-to-use SVG templates:

Need	Pattern
Steps in a process	Horizontal Flowchart
Events over time	Vertical Timeline
Ranking / metrics	Horizontal Bar Chart
Prioritisation	2×2 Comparison Grid
Team / structure	Org / Hierarchy Chart

Rules:

One diagram per slide, never combined with a bullet list
Use currentColor so diagrams inherit the slide's text color automatically
Apply --accent color to the most important element (first step, top bar, highlighted quadrant)
Never use Mermaid.js, Chart.js, or any external library — inline SVG only

Image Pipeline (skip if no images)

For each USABLE image from Step 1.2, determine processing needed (circular crop for logos, resize for large files, padding for screenshots needing breathing room) and run it with Pillow. Reference images with relative paths (assets/...) — don't base64 encode unless the user explicitly wants a fully self-contained file.

Rules:

Never repeat an image across slides (logos may bookend title + closing)
Always add style-matched CSS framing (border/glow matching the style's accent color) when image colors clash with the palette

Code Quality

Comment every section: what it does, why it exists, how to modify it
Semantic HTML (<section>, <nav>, <main>)
ARIA labels on nav elements and interactive controls
@media (prefers-reduced-motion: reduce) support
No markdown symbols (#, *, **, _) in slide text — use semantic HTML elements (<strong>, <em>, <h2>) for structure and emphasis

Phase 4: PPT Conversion

Read references/pptx-extraction.md for the Python extraction script.

Run the extraction script to get slides_data (title, content, images, notes per slide)
Present extracted structure to user, confirm it looks right
Run Phase 2 (Style Discovery) with extracted content in mind
Generate HTML preserving all text, images (from assets/), and slide order. Put speaker notes in data-notes attributes on each .slide section (not HTML comments) so they work in Presenter Mode.

Phase 5: Delivery

Clean up: delete .claude-design/slide-previews/ if it exists.
Embed speaker notes in HTML — every .slide section must have a data-notes="..." attribute with 2-4 sentences (what to say, key emphasis, transition cue). These power the built-in Presenter Mode.
Generate PRESENTATION_SCRIPT.md if deck has 8+ slides or was created from PLANNING.md (same notes content, formatted as a readable document).
Open: open [filename].html
Summarize:

Your presentation is ready!

📁 File: [filename].html
🎨 Style: [Style Name]
📊 Slides: [count]

Navigation: Arrow keys or Space · Scroll or swipe · Click dots to jump
Presenter Mode: press P to open the presenter window (notes + timer + controls)

To customize: edit :root variables at the top of the CSS for colors, fonts, and spacing.

To export as PPTX: run `/slide-creator --export pptx` (requires Python 3 + playwright + python-pptx, no Node.js)

Always mention: hover the top-left corner or press E to enter edit mode (included by default unless user explicitly opted out).

Effect → Feeling Guide

Feeling	Techniques
Dramatic/Cinematic	Slow fade-ins 1-1.5s, dark backgrounds, full-bleed images, parallax
Techy/Futuristic	Neon glow, particle canvas, grid patterns, monospace accents, glitch text effects
Playful/Friendly	Bouncy easing, large rounded corners, pastels, floating/bobbing animations
Professional	Subtle 200-300ms animations, clean sans-serif, minimal decoration, data-focus
Calm/Minimal	Very slow motion, high whitespace, muted palette, generous padding, serif type
Editorial	Strong typography hierarchy, pull quotes, serif headlines, one accent color

Example: New Presentation

"Make a pitch deck for my AI startup"
Single form → purpose=pitch, length=medium, content=rough notes, images=./assets, editing=yes
User shares notes; skill evaluates assets (4 USABLE, 1 blurry — excluded with explanation)
Slide outline co-designed around text + images; confirmed via AskUserQuestion
Mood=Impressed+Excited → 3 previews generated → user picks Neon Cyber
Pillow processes images; HTML generated with full viewport CSS + JS suite
Browser opens; user requests tweaks; final deck delivered

Example: PPT Conversion

"Convert slides.pptx to a web presentation"
Run extraction script → present extracted content → user confirms
Style Discovery (Phase 2) → HTML generation with preserved assets
Final presentation delivered

Related Skills

frontend-design — For interactive pages that go beyond slides
design-and-refine:design-lab — For iterating on component designs

About this skill

Automatic

Marketing & Content pack

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 7/30/2026

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/html-slide-creator/SKILL.md

View on GitHub ↗

License MIT LicenseImported 8/2/2026Version v1Bundled 15 files · scripts

Illustrative Want to see what slide-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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SkillScore

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What it changes

Track record

Use this skill

Slide Creator

Core Philosophy

Command Flags

Planning Mode (--plan)

Export Mode (--export pptx)

Phase 0: Detect Mode

Phase 1: Content Discovery

Image Evaluation

Phase 2: Style Discovery

Style Path

Generate Previews

Phase 3: Generate Presentation

If Blue Sky style is selected → use the starter template

If a custom theme from themes/ is selected

For all other styles → read the standard references

Viewport Fitting

Diagram Slides (when content calls for a visual relationship)

Image Pipeline (skip if no images)

Code Quality

Phase 4: PPT Conversion

Phase 5: Delivery

Effect → Feeling Guide

Example: New Presentation

Example: PPT Conversion

Related Skills

SkillSafety

Source

Other skills for the same job

More in the registry

Planning Mode (`--plan`)

Export Mode (`--export pptx`)