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usefigma — Figma Plugin API Skill for Slides · devin-axis | DecimalAI

Design & Mediaby devin-axis

usefigma — Figma Plugin API Skill for Slides

This skill helps agents use Figma's use_figma MCP tool in the Slides context. Can be used alongside figma-use which has foundational context for using the use_figma tool.

Never made a case worseMaintained

SkillScore

SkillScore68/100

Test results 68

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

23%68%of test cases passed +45 pts

Without skill5 of 22

With skill15 of 22

10 fixed5 passed either way7 still failing0 broke

Measured on gemini-3.6-flash9/8/2026v119 comparable

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskWhen invoking the use_figma MCP tool for a presentation task where the skill was loaded from an MCP resource, how should the skillNames parameter be formatted?

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 devin-axis-figma-use-slides
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("devin-axis-figma-use-slides")
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 devin-axis-figma-use-slides

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/devin-axis-figma-use-slides/SKILL.md https://app.decimal.ai/s/devin-axis-figma-use-slides/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/devin-axis-figma-use-slides/SKILL.md

This gets SKILL.md only. The skill's 6 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 devin-axis-figma-use-slides

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("devin-axis-figma-use-slides")
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/devin-axis-figma-use-slides/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/devin-axis-figma-use-slides/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 6 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 devin-axis-figma-use-slides

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("devin-axis-figma-use-slides")
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/devin-axis-figma-use-slides/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/devin-axis-figma-use-slides/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 6 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 devin-axis-figma-use-slides

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("devin-axis-figma-use-slides")
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/devin-axis-figma-use-slides/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/devin-axis-figma-use-slides/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 6 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 devin-axis-figma-use-slides

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("devin-axis-figma-use-slides")
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/devin-axis-figma-use-slides/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/devin-axis-figma-use-slides/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 6 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 devin-axis-figma-use-slides

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("devin-axis-figma-use-slides")
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/devin-axis-figma-use-slides/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/devin-axis-figma-use-slides/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 6 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 devin-axis-figma-use-slides

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("devin-axis-figma-use-slides")
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/devin-axis-figma-use-slides/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/devin-axis-figma-use-slides/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 6 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 devin-axis-figma-use-slides

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("devin-axis-figma-use-slides")
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/devin-axis-figma-use-slides/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 6 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 devin-axis-figma-use-slides

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("devin-axis-figma-use-slides")
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/devin-axis-figma-use-slides/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/devin-axis-figma-use-slides/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 6 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 devin-axis-figma-use-slides

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("devin-axis-figma-use-slides")
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/devin-axis-figma-use-slides/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/devin-axis-figma-use-slides/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 6 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 devin-axis-figma-use-slides

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("devin-axis-figma-use-slides")
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/devin-axis-figma-use-slides/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/devin-axis-figma-use-slides/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 6 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 devin-axis-figma-use-slides

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("devin-axis-figma-use-slides")
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/devin-axis-figma-use-slides/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/devin-axis-figma-use-slides/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 6 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 devin-axis-figma-use-slides

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("devin-axis-figma-use-slides")
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/devin-axis-figma-use-slides/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/devin-axis-figma-use-slides/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 6 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 devin-axis-figma-use-slides

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/devin-axis-figma-use-slides/SKILL.md https://app.decimal.ai/s/devin-axis-figma-use-slides/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/devin-axis-figma-use-slides/SKILL.md

This gets SKILL.md only. The skill's 6 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/devin-axis-figma-use-slides/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/devin-axis-figma-use-slides.json

This gets SKILL.md only. The skill's 6 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 9/8/2026
Source: devin-axis/ipollowork ↗
License: NOASSERTION

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

use_figma — Figma Plugin API Skill for Slides

This skill contains Slides-specific context for the use_figma MCP tool. The figma-use skill provides foundational context for plugin API execution via MCP as well as the full Figma plugin API for more advanced use-cases that are not described here.

Always include figma-use-slides in the comma-separated skillNames parameter when calling use_figma for Slides operations. If this skill was loaded via an MCP resource, you MUST prefix the name with resource: (e.g. resource:figma-use-slides). This is a logging parameter used to track skill usage — it does not affect execution.

Choosing How to Build a Slides Deck

If your environment also provides a generate_deck tool, choose one approach per deck request — do not call both for the same deck.

When to use which

use_figma + this skill (default): Handles any Slides task — new decks, edits to existing decks, brand-matched designs, reference-file styling, iterative refinement, speaker notes, and full creative control over layout, color, and typography. Use this for most requests.

generate_deck: Generates a complete deck in a single call using prebuilt, curated templates. Useful for quick, straightforward decks where the user doesn't need custom design, brand matching, or reference-file styling. It cannot use custom templates, cannot reference other Figma files for design direction, and does not support iterative editing or follow-up modifications through the conversation.

When in doubt, default to use_figma + this skill — it covers everything generate_deck can do and more.

Pick one and commit

Once you choose an approach for a deck, complete the entire request with that approach. Do not generate a deck with generate_deck and then also create or populate a file with use_figma — the user ends up with duplicate, conflicting artifacts and a confusing experience.

Critical Rules (Slides-specific)

Newly created Slides files have a default light theme. When a Slides file is created via create_new_file, a default light theme is automatically initialized. This theme is structural scaffolding — you should overwrite the theme's color variables and text styles with your own design direction for the deck you're building. Do not rely on or be influenced by the default light theme tokens.
MUST appendChild BEFORE setting x/y — for every node, at every level of nesting. Newly created nodes are silently auto-parented to a slide context at absolute (240, 240) (the slide grid's GRID_PADDING). Writing x/y before appendChild causes the value to be stored against that hidden origin; the node then lands at (intended − 240, intended − 240) once you attach the real parent. The bug is intermittent — some frames in the same script escape it, so a working test is not proof you're safe. Signature to recognize: if any node ends up (−240, −240) from where you set it, your code set x/y before the final appendChild. Do NOT try to compensate by adding 240 back — that produces worse output on retry. Fix the order instead. See slide-gotchas.md for the helper pattern that makes the order impossible to get wrong.
SLIDE_GRID and SLIDE_ROW are opaque nodes — do not access .fills, .effects, or layout properties on them. Only SLIDE nodes (type 'SLIDE') extend BaseFrameMixin. Exception: SLIDE_ROW.name IS settable — that's how plugins rename slide sections (e.g. slideRow.name = "Intro"). See slide-lifecycle.md.
get_metadata does NOT work on Slides files. Use use_figma read-only scripts for validation. Return created node positions in closePlugin() output and verify no overlapping bounding boxes.
Do NOT call figma.createPage() in Slides. It throws TypeError: figma.createPage no such property 'createPage' on the figma global object — createPage() is a Design-file API only (figma.com/design/...); the Slides URL is figma.com/slides/.... Use the slide grid (SLIDE_GRID / SLIDE_ROW / SLIDE) to organize deck structure instead — see slide-lifecycle.md and slide-grid.md.
Never delete existing slides to rebuild them. When asked to improve, redesign, or restyle a deck, modify the existing slides in place. Only delete slides when the user explicitly asks to "start over" or "redo from scratch."

Design Thinking

Not every task needs the same depth of design thinking. Before doing anything, identify which gear you're in:

Content/property edits — changing text, swapping a color, updating a number, fixing alignment, resizing an element. Skip design thinking. Just make the change and match what's already there.
Structural additions — adding slides, reworking a section's layout, changing the deck's color palette, introducing a new visual element. This includes requests to "improve," "redesign," or "restyle" a deck — those are in-place edits to what's already there, not a new deck. Design thinking applies, but in inherit mode: the existing deck is your design language. Inspect it, match its palette, type, spatial habits, and motifs. Extend the deck's existing character rather than reinventing it.
New deck creation — building a deck from scratch or from a blank file. Full design thinking applies as described below.

For structural additions to existing decks: run the inspection scripts (below) and take screenshots before making changes. The answers to "what color story?" and "what type treatment?" are already in the file — your job is to read them and stay consistent. The design principles in slide-design.md describe what you're matching, not what you're choosing.

New deck design process

Before writing any Plugin API code for a new deck, decide what it should feel like. Figma users have high visual expectations — a deck that looks like it came out of a generic template generator will stand out for the wrong reasons.

Read the brief. What is the deck communicating, and to whom? An investor pitch, a team retrospective, a product launch, and a technical deep-dive all demand different visual treatments. The design should be inseparable from the content.
Check for a design language. Before inventing anything, look at what the user already gave you. Brand guidelines in the prompt — color palettes, typography specs, logo rules, tone descriptors — are design decisions that have already been made. A link to a reference Figma file is a design language you should study, not glance at. The more specific the user's inputs, the less you should invent on your own. When the user provides a reference, your job shifts from designer to interpreter: extract the design language and apply it faithfully to new content.
Take a position — on what's left. If the user supplied a full brand system, your creative latitude is in layout, pacing, and composition — not in color or type. If they gave you a single reference slide for inspiration, you have more room but should still echo its character. If they gave you nothing, then you own every decision — choose a color story, a type treatment, a way of organizing space, and follow through on it across every slide. A deck with a clear perspective (even a quiet one) always reads better than one that plays it safe on every decision. The scope of "take a position" scales inversely with what the user provided.
Give it a signature. Every good deck has at least one element you'd recognize if you saw it out of context: a distinctive palette, an unexpected layout cadence, a recurring shape language. When working from brand guidelines, the signature should come from that brand language — amplify something that's already there rather than adding something foreign. When designing from scratch, decide what the signature is before you start building.

Reading a reference file

When the user provides a link to a Figma file as a reference, study it before designing anything. What you extract depends on what the file is:

A Slides file: get_metadata does not work on Slides files. Use get_screenshot to capture individual slides for visual reference, and use_figma with the reference file's fileKey to run read-only scripts that extract theme variables, color palettes, font choices, and layout patterns.
A Design file: get_design_context gives you comprehensive design data — colors, typography, layout structure. get_screenshot gives you visual reference. Use both.

What to look for in a reference file: the color palette (which hue leads, what the accent is, how dark/light backgrounds are used), the type choices (families, weights, how hierarchy is handled), the spatial habits (where content anchors, how much whitespace, whether things bleed off edges), and any recurring motifs (shapes, line treatments, decorative elements). These are the decisions you inherit — everything else is yours.

How closely to follow the reference depends on what the user asked for. "Make it look like this" means replicate the design language with new content. "Use this for inspiration" means echo the character but make it your own. "Here's our brand deck" means extract the brand system and apply it consistently. When in doubt, stay closer to the reference — it's easier for a user to ask you to diverge than to ask you to undo invented choices that conflict with their brand.

Load slide-design.md for specific guidance on color, type, layout patterns, composition, and what to avoid. When you have a reference file or brand guidelines, treat slide-design.md's principles as defaults for the decisions the user didn't make — not as overrides for the ones they did.

Deck-Building Workflow

When building a new deck of 5 or more slides, use this two-phase workflow. It replaces the general incremental workflow from figma-use Section 6 for deck-building specifically — the principles still apply, but the cadence changes.

Phase 1 — Design & Plan

Complete the design thinking process above (read the brief, check for a design language, take a position, give it a signature), then before writing any use_figma code, produce a slide plan covering the entire deck:

Slide-by-slide plan. For every slide: its purpose/content, layout approach described spatially (e.g. "title anchored upper-left, spec card filling the right third, decorative circle bleeding off top-right edge"), and background treatment (dark/light/gradient). Do NOT compute pixel coordinates during planning — describe layouts in spatial terms. Coordinate math happens during code generation.
Shared constants. Declare the font families and styles you'll use, the color palette as named roles (primary, accent, bgDark, surface, textPrimary, textMuted, etc.), and the recurring motif or signature element.
Layout variety check. Read through the slide plans in sequence. If the layout descriptions feel repetitive — "two-column, two-column, grid, two-column" — rearrange before building. This is the cheapest moment to diversify. See slide-design.md for anti-patterns.
Code preamble. Write out the reusable preamble you'll paste at the top of every build script: a const C = { ... } color palette object, a Promise.all([...]) font-loading block, and the addFrame/addText/addRect helpers from slide-gotchas.md.

Phase 2 — Build

Execute the plan in large batches. The goal is to minimize the number of think-then-build cycles — not to minimize elements per script.

3–5 slides per use_figma call. Structurally similar slides (e.g. a series of product feature slides) can go in the same batch. Each slide is an isolated subtree — cross-slide dependencies don't exist, so large batches are safe.
Do NOT re-plan between batches. The design was decided in Phase 1. If a batch succeeds and passes validation, move to the next batch immediately. Only re-plan if a batch fails or produces a visual problem that requires changing the approach.
Paste the code preamble (colors, fonts, helpers) at the top of every build script. Copy it from Phase 1 verbatim — do not re-derive it.
Validate every batch with the deterministic batch validation script from slide-gotchas.md. This checks for overlapping elements, text clipping, and out-of-bounds nodes in ~3 seconds. If the check passes, proceed without a screenshot. If it fails, screenshot the affected slides and fix before continuing.
Screenshot at checkpoints only — after the first batch (validates the visual system: colors, typography, design direction), and after the final batch (overall quality). Take a screenshot of 1–2 representative slides per checkpoint using inline await slide.screenshot(), not separate get_screenshot calls.
Return all created node IDs from every build script, as always.

Sections

A section is a horizontal row in the slide grid — every row is a section. Names show up in the editor (next to the row) and in Presenter View (so speakers can jump between groups). They're an organizational aid for whoever is editing the deck — the user owns where the breaks fall, not you.

When asked to organize a deck

"Organize this deck" is ambiguous — grouping, reordering, deduping, or restructuring. Read the deck before reaching for AskUserQuestion.

Default: propose, don't ask. Most decks have cues — title bookend, numbered use cases, repeated Before / After pairs, transition slides ("Then X enters the chat"), a Thank you. When cues exist, pick a sectioning and surface it in one confirmation message. Bounded calls inside the proposal (one Use Cases row vs. three, where a transition slide lives) are reversible — pick one and move on.

Fallback: ask when cues are absent. If slides are in arbitrary order or there's no spine, ask which ranges go together and what to call them. Don't slice by thirds as a substitute for reading.

Naming + scoping

Names should be short (1–3 words), concrete (Demo beats Show & tell), and consistent within a deck. Two to five sections is typical; more only for long or repeating decks. Names aren't slide titles — they help find a group, not describe its content.

Renaming a section

getSlideGrid() returns SlideNode[][] — the inner arrays are plain JS arrays of slides, NOT SLIDE_ROW nodes. Setting .name on those arrays silently no-ops. To rename a section, traverse the node tree and set .name on the actual SLIDE_ROW:

const slideGrid = figma.currentPage.children.find(c => c.type === "SLIDE_GRID");
slideGrid.children[0].name = "Intro";

Speaker Notes

Speaker notes are the presenter's private companion to each slide. They appear in Presenter View (visible only to the speaker, not the audience) and serve as a script, cue sheet, or talking-points reference during a live presentation.

When to write speaker notes

When asked: If the user asks for speaker notes, presenter notes, talking points, or a script for a deck, write notes for every slide that has substantive content (skip section dividers or purely decorative slides unless there's something to say).
Presenter-ready decks: If the user explicitly asks for a deck that is ready to present live, speaker notes are useful. Add them when they help the presenter understand pacing, transitions, or context that is not visible on the slide.
Sparse or visual slides: If a slide is built around a chart, image, metaphor, or provocative question, notes can help explain what the presenter should say. Use screenshots or node.screenshot() for image-heavy, chart-heavy, or visually sparse slides when visual context matters, but don't screenshot every slide by default — images spend context budget.
Don't add notes unprompted: For normal slide edits, layout work, or updates to existing decks, do not populate speaker notes unless the user asks. Adding notes changes the presentation flow and can surprise the deck owner.

What good speaker notes look like

Speaker notes are for the presenter, not the audience. They should feel like a trusted colleague leaning over and whispering "here's what to say." Good notes:

Complement the slide, not repeat it. If the slide says "Revenue grew 40%", the notes shouldn't say "Revenue grew 40%." They should say why it grew, what the audience should take away, or what question this usually prompts.
Are concise and scannable. A presenter glancing down mid-sentence needs to find their place instantly. Use short bullet points, not dense paragraphs. Each point should be one idea.
Include transitions. The best notes tell the presenter how to move between slides: "After the applause dies down..." or "This builds on the previous point — call back to the 40% figure."
Carry context the slide can't. Data sources ("Source: Q4 FY25 internal metrics, not yet public"), caveats ("Skip this slide if the CFO is in the room"), timing cues ("This is the halfway point — you should be at ~10 minutes"), and anticipated questions ("They'll ask about margins — see appendix slide 14").
Match the presentation's register. Notes for an investor pitch are precise and rehearsed. Notes for a team retro are casual and flexible. Notes for a keynote might include stage directions. Match the tone to the context.

What to avoid in speaker notes

Full scripts: Wall-of-text notes encourage reading verbatim, which makes for a terrible presentation. If the user explicitly asks for a script, write one, but default to bullet points.
Formatting for the audience: Notes aren't visible to the audience. Don't optimize them for readability by non-presenters.
Redundancy with the slide: If the slide is self-explanatory ("Thank You" with contact info), notes aren't needed. It's fine to leave a slide's notes empty.

Formatting

slide.speakerNotes accepts a markdown string. Prefer bullet lists as the primary structure; bold is useful for emphasis on key phrases the presenter shouldn't skip. See slide-properties.md for the full list of supported (lists, bold, italic, strikethrough) and unsupported (headings, code blocks, inline code, links) markdown.

Inspecting Slides Files

There is no dedicated read tool for Slides files yet. Use use_figma with read-only scripts for inspection, and get_screenshot / await node.screenshot() for visual context.

Inspect before creating. Before creating anything, run a read-only use_figma to discover what already exists — slides, text, components, naming conventions. The figma-use Section 6 "Inspect first" pattern applies here.
get_metadata does NOT work on Slides files — it only supports figma (Design) editor type.
console.log() output is NOT returned — only the return value comes back. Always return the data you need.
Use get_screenshot for visual context — pass a valid nodeId to get a screenshot. You can also use await node.screenshot() inline within use_figma scripts.

Quick inspection scripts

List all slides in the deck:

const grid = figma.getSlideGrid();
return grid.map((row, rowIdx) =>
  row.map((slide, colIdx) => ({
    id: slide.id,
    name: slide.name,
    row: rowIdx,
    col: colIdx,
    isSkipped: slide.isSkippedSlide,
    speakerNotes: slide.speakerNotes,
  }))
);

Get text content from a specific slide:

const slide = figma.getNodeById("TARGET_SLIDE_ID");
// findAllWithCriteria uses an indexed type lookup — much faster than
// findAll(n => n.type === 'TEXT') on slides with many shapes/images.
const textNodes = slide.findAllWithCriteria({ types: ["TEXT"] });
const fontsToLoad = new Set();
for (const t of textNodes) {
  if (t.fontName !== figma.mixed) {
    fontsToLoad.add(JSON.stringify(t.fontName));
  } else {
    const segments = t.getStyledTextSegments(["fontName"]);
    for (const seg of segments) fontsToLoad.add(JSON.stringify(seg.fontName));
  }
}
for (const f of fontsToLoad) {
  await figma.loadFontAsync(JSON.parse(f));
}
return textNodes.map(t => ({
  id: t.id,
  name: t.name,
  characters: t.characters,
  x: t.x,
  y: t.y,
  width: t.width,
  height: t.height,
}));

Reference Docs

Load only the references your task needs:

slide-gotchas — Pitfalls specific to Slides (coordinate offsets, opaque node types, validation workarounds)
slide-lifecycle — Create, clone, delete, and reorder slides and slide rows
slide-grid — Work with the slide grid layout (getSlideGrid, setSlideGrid)
slide-content — Build content within slides (text, shapes, auto-layout — SlideNode extends BaseFrameMixin)
slide-properties — Slide-specific properties (speakerNotes, isSkippedSlide, focusedSlide, focusedNode, slideThemeId, InteractiveSlideElementNode)
slide-design — Design principles for visually interesting, varied decks (color strategy, typography, layout variety, spatial composition, anti-patterns)

About this skill

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Source

Imported

devin-axis / ipollowork

examples/plugin-packages/figma/skills/figma-use-slides/SKILL.md

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License NOASSERTIONImported 8/17/2026Version v1Bundled 6 files

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Use this skill

use_figma — Figma Plugin API Skill for Slides

Choosing How to Build a Slides Deck

When to use which

Pick one and commit

Critical Rules (Slides-specific)

Design Thinking

New deck design process

Reading a reference file

Deck-Building Workflow

Phase 1 — Design & Plan

Phase 2 — Build

Sections

When asked to organize a deck

Naming + scoping

Renaming a section

Speaker Notes

When to write speaker notes

What good speaker notes look like

What to avoid in speaker notes

Formatting

Inspecting Slides Files

Quick inspection scripts

Reference Docs

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