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Venue Templates · foryourhealth111-pixel | DecimalAI

Documentationby foryourhealth111-pixel

Venue Templates

Use when preparing manuscripts, conference papers, or academic posters that need venue-specific templates, LaTeX style files, author guidelines, page limits, anonymity rules, camera-ready formatting, or submission compliance checks.

Never made a case worse

SkillScore

SkillScore87/100

Test results 87

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

39%87%of test cases passed +48 pts

Without skill9 of 23

With skill20 of 23

11 fixed9 passed either way3 still failing0 broke

Measured on gemini-3.6-flash8/13/2026v1

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskWhat command retrieves the venue formatting requirements directly for NeurIPS using the bundled CLI script?

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 foryourhealth111-pixel-venue-templates
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("foryourhealth111-pixel-venue-templates")
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 foryourhealth111-pixel-venue-templates

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/foryourhealth111-pixel-venue-templates/SKILL.md https://app.decimal.ai/s/foryourhealth111-pixel-venue-templates/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/foryourhealth111-pixel-venue-templates/SKILL.md

This gets SKILL.md only. The skill's 7 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 foryourhealth111-pixel-venue-templates

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("foryourhealth111-pixel-venue-templates")
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/foryourhealth111-pixel-venue-templates/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/foryourhealth111-pixel-venue-templates/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 7 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 foryourhealth111-pixel-venue-templates

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("foryourhealth111-pixel-venue-templates")
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/foryourhealth111-pixel-venue-templates/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/foryourhealth111-pixel-venue-templates/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 7 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 foryourhealth111-pixel-venue-templates

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("foryourhealth111-pixel-venue-templates")
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/foryourhealth111-pixel-venue-templates/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/foryourhealth111-pixel-venue-templates/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 7 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 foryourhealth111-pixel-venue-templates

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("foryourhealth111-pixel-venue-templates")
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/foryourhealth111-pixel-venue-templates/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/foryourhealth111-pixel-venue-templates/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 7 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 foryourhealth111-pixel-venue-templates

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("foryourhealth111-pixel-venue-templates")
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/foryourhealth111-pixel-venue-templates/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/foryourhealth111-pixel-venue-templates/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 7 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 foryourhealth111-pixel-venue-templates

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("foryourhealth111-pixel-venue-templates")
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/foryourhealth111-pixel-venue-templates/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/foryourhealth111-pixel-venue-templates/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 7 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 foryourhealth111-pixel-venue-templates

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("foryourhealth111-pixel-venue-templates")
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/foryourhealth111-pixel-venue-templates/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 7 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 foryourhealth111-pixel-venue-templates

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("foryourhealth111-pixel-venue-templates")
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/foryourhealth111-pixel-venue-templates/SKILL.md

Give it to your agent

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

skill = Path(".agents/skills/foryourhealth111-pixel-venue-templates/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 7 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 foryourhealth111-pixel-venue-templates

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("foryourhealth111-pixel-venue-templates")
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/foryourhealth111-pixel-venue-templates/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/foryourhealth111-pixel-venue-templates/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 7 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 foryourhealth111-pixel-venue-templates

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("foryourhealth111-pixel-venue-templates")
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/foryourhealth111-pixel-venue-templates/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/foryourhealth111-pixel-venue-templates/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 7 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 foryourhealth111-pixel-venue-templates

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("foryourhealth111-pixel-venue-templates")
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/foryourhealth111-pixel-venue-templates/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/foryourhealth111-pixel-venue-templates/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 7 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 foryourhealth111-pixel-venue-templates

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("foryourhealth111-pixel-venue-templates")
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/foryourhealth111-pixel-venue-templates/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/foryourhealth111-pixel-venue-templates/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 7 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 foryourhealth111-pixel-venue-templates

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/foryourhealth111-pixel-venue-templates/SKILL.md https://app.decimal.ai/s/foryourhealth111-pixel-venue-templates/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/foryourhealth111-pixel-venue-templates/SKILL.md

This gets SKILL.md only. The skill's 7 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/foryourhealth111-pixel-venue-templates/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/foryourhealth111-pixel-venue-templates.json

This gets SKILL.md only. The skill's 7 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 8/13/2026
Source: foryourhealth111-pixel/vibe-skills ↗
License: Apache-2.0

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

Venue Templates

Overview

Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues, academic conferences, and research posters. This skill provides ready-to-use templates and detailed specifications for academic publication submissions.

Use this skill when preparing manuscripts for journal submission, conference papers, or research posters and need venue-specific formatting requirements and templates.

When to Use This Skill

This skill should be used when:

Preparing a manuscript for submission to a specific journal (Nature, Science, PLOS, IEEE, etc.)
Writing a conference paper with specific formatting requirements (NeurIPS, ICML, CHI, etc.)
Creating an academic research poster for conferences
Checking formatting requirements and page limits for target venues
Customizing templates with author information and project details
Verifying document compliance with venue specifications

Boundary

This skill owns venue requirements and template compliance. It does not generate figures, write manuscript prose, manage bibliography libraries, prepare rebuttal responses, or draft grants.

Core Capabilities

1. Journal Article Templates

Access LaTeX templates and formatting guidelines for 50+ major scientific journals across disciplines:

Nature Portfolio:

Nature, Nature Methods, Nature Biotechnology, Nature Machine Intelligence
Nature Communications, Nature Protocols
Scientific Reports

Science Family:

Science, Science Advances, Science Translational Medicine
Science Immunology, Science Robotics

PLOS (Public Library of Science):

PLOS ONE, PLOS Biology, PLOS Computational Biology
PLOS Medicine, PLOS Genetics

Cell Press:

Cell, Neuron, Immunity, Cell Reports
Molecular Cell, Developmental Cell

IEEE Publications:

IEEE Transactions (various disciplines)
IEEE Access, IEEE Journal templates

ACM Publications:

ACM Transactions, Communications of the ACM
ACM conference proceedings

Other Major Publishers:

Springer journals (various disciplines)
Elsevier journals (custom templates)
Wiley journals
BMC journals
Frontiers journals

2. Conference Paper Templates

Conference-specific templates with proper formatting for major academic conferences:

Machine Learning & AI:

NeurIPS (Neural Information Processing Systems)
ICML (International Conference on Machine Learning)
ICLR (International Conference on Learning Representations)
CVPR (Computer Vision and Pattern Recognition)
AAAI (Association for the Advancement of Artificial Intelligence)

Computer Science:

ACM CHI (Human-Computer Interaction)
SIGKDD (Knowledge Discovery and Data Mining)
EMNLP (Empirical Methods in Natural Language Processing)
SIGIR (Information Retrieval)
USENIX conferences

Biology & Bioinformatics:

ISMB (Intelligent Systems for Molecular Biology)
RECOMB (Research in Computational Molecular Biology)
PSB (Pacific Symposium on Biocomputing)

Engineering:

IEEE conference templates (various disciplines)
ASME, AIAA conferences

3. Research Poster Templates

Academic poster templates for conference presentations:

Standard Formats:

A0 (841 × 1189 mm / 33.1 × 46.8 in)
A1 (594 × 841 mm / 23.4 × 33.1 in)
36" × 48" (914 × 1219 mm) - Common US size
42" × 56" (1067 × 1422 mm)
48" × 36" (landscape orientation)

Template Packages:

beamerposter: Classic academic poster template
tikzposter: Modern, colorful poster design
baposter: Structured multi-column layout

Design Features:

Optimal font sizes for readability at distance
Color schemes (colorblind-safe palettes)
Grid layouts and column structures
QR code integration for supplementary materials

Workflow: Finding and Using Templates

Step 1: Identify Target Venue

Determine the specific publication venue, conference, or funding agency:

Example queries:
- "I need to submit to Nature"
- "What are the requirements for NeurIPS 2025?"
- "Show me NSF proposal formatting"
- "I'm creating a poster for ISMB"

Step 2: Query Template and Requirements

Access venue-specific templates and formatting guidelines:

For Journals:

# Load journal formatting requirements
Reference: references/journals_formatting.md
Search for: "Nature" or specific journal name

# Retrieve template
Template: assets/journals/nature_article.tex

For Conferences:

# Load conference formatting
Reference: references/conferences_formatting.md
Search for: "NeurIPS" or specific conference

# Retrieve template
Template: assets/journals/neurips_article.tex

For Posters:

# Load poster guidelines
Reference: references/posters_guidelines.md

# Retrieve template
Template: assets/posters/beamerposter_academic.tex

For Grants:

# Load grant requirements
Reference: references/grants_requirements.md
Search for: "NSF" or specific agency

# Retrieve template
Template: assets/grants/nsf_proposal_template.tex

Step 3: Review Formatting Requirements

Check critical specifications before customizing:

Key Requirements to Verify:

Page limits (varies by venue)
Font size and family
Margin specifications
Line spacing
Citation style (APA, Vancouver, Nature, etc.)
Figure/table requirements
File format (PDF, Word, LaTeX source)
Anonymization (for double-blind review)
Supplementary material limits

Step 4: Customize Template

Use helper scripts or manual customization:

Option 1: Helper Script (Recommended):

python scripts/customize_template.py \
  --template assets/journals/nature_article.tex \
  --title "Your Paper Title" \
  --authors "First Author, Second Author" \
  --affiliations "University Name" \
  --output my_nature_paper.tex

Option 2: Manual Editing:

Open template file
Replace placeholder text (marked with comments)
Fill in title, authors, affiliations, abstract
Add your content to each section

Step 5: Validate Format

Check compliance with venue requirements:

python scripts/validate_format.py \
  --file my_paper.pdf \
  --venue "Nature" \
  --check-all

Validation Checks:

Page count within limits
Font sizes correct
Margins meet specifications
References formatted correctly
Figures meet resolution requirements

Step 6: Compile and Review

Compile LaTeX and review output:

# Compile LaTeX
pdflatex my_paper.tex
bibtex my_paper
pdflatex my_paper.tex
pdflatex my_paper.tex

# Or use latexmk for automated compilation
latexmk -pdf my_paper.tex

Review checklist:

All sections present and properly formatted
Citations render correctly
Figures appear with proper captions
Page count within limits
Author guidelines followed
Supplementary materials prepared (if needed)

Template Categories

By Document Type

Category	Template Count	Common Venues
Journal Articles	30+	Nature, Science, PLOS, IEEE, ACM, Cell Press
Conference Papers	20+	NeurIPS, ICML, CVPR, CHI, ISMB
Research Posters	10+	A0, A1, 36×48, various packages
Grant Proposals	15+	NSF, NIH, DOE, DARPA, foundations

By Discipline

Discipline	Supported Venues
Life Sciences	Nature, Cell Press, PLOS, ISMB, RECOMB
Physical Sciences	Science, Physical Review, ACS, APS
Engineering	IEEE, ASME, AIAA, ACM
Computer Science	ACM, IEEE, NeurIPS, ICML, ICLR
Medicine	NEJM, Lancet, JAMA, BMJ
Interdisciplinary	PNAS, Nature Communications, Science Advances

Helper Scripts

query_template.py

Search and retrieve templates by venue name, type, or keywords:

# Find templates for a specific journal
python scripts/query_template.py --venue "Nature" --type "article"

# Search by keyword
python scripts/query_template.py --keyword "machine learning"

# List all available templates
python scripts/query_template.py --list-all

# Get requirements for a venue
python scripts/query_template.py --venue "NeurIPS" --requirements

customize_template.py

Customize templates with author and project information:

# Basic customization
python scripts/customize_template.py \
  --template assets/journals/nature_article.tex \
  --output my_paper.tex

# With author information
python scripts/customize_template.py \
  --template assets/journals/nature_article.tex \
  --title "Novel Approach to Protein Folding" \
  --authors "Jane Doe, John Smith, Alice Johnson" \
  --affiliations "MIT, Stanford, Harvard" \
  --email "[email protected]" \
  --output my_paper.tex

# Interactive mode
python scripts/customize_template.py --interactive

validate_format.py

Check document compliance with venue requirements:

# Validate a compiled PDF
python scripts/validate_format.py \
  --file my_paper.pdf \
  --venue "Nature" \
  --check-all

# Check specific aspects
python scripts/validate_format.py \
  --file my_paper.pdf \
  --venue "NeurIPS" \
  --check page-count,margins,fonts

# Generate validation report
python scripts/validate_format.py \
  --file my_paper.pdf \
  --venue "Science" \
  --report validation_report.txt

Best Practices

Template Selection

Verify currency: Check template date and compare with latest author guidelines
Check official sources: Many journals provide official LaTeX classes
Test compilation: Compile template before adding content
Read comments: Templates include helpful inline comments

Customization

Preserve structure: Don't remove required sections or packages
Follow placeholders: Replace marked placeholder text systematically
Maintain formatting: Don't override venue-specific formatting
Keep backups: Save original template before customization

Compliance

Check page limits: Verify before final submission
Validate citations: Use correct citation style for venue
Test figures: Ensure figures meet resolution requirements
Review anonymization: Remove identifying information if required

Submission

Follow instructions: Read complete author guidelines
Include all files: LaTeX source, figures, bibliography
Generate properly: Use recommended compilation method
Check output: Verify PDF matches expectations

Common Formatting Requirements

Page Limits (Typical)

Venue Type	Typical Limit	Notes
Nature Article	5 pages	~3000 words excluding refs
Science Report	5 pages	Figures count toward limit
PLOS ONE	No limit	Unlimited length
NeurIPS	8 pages	+ unlimited refs/appendix
ICML	8 pages	+ unlimited refs/appendix
NSF Proposal	15 pages	Project description only
NIH R01	12 pages	Research strategy

Citation Styles by Venue

Venue	Citation Style	Format
Nature	Numbered (superscript)	Nature style
Science	Numbered (superscript)	Science style
PLOS	Numbered (brackets)	Vancouver
Cell Press	Author-year	Cell style
ACM	Numbered	ACM style
IEEE	Numbered (brackets)	IEEE style
APA journals	Author-year	APA 7th

Figure Requirements

Venue	Resolution	Format	Color
Nature	300+ dpi	TIFF, EPS, PDF	RGB or CMYK
Science	300+ dpi	TIFF, PDF	RGB
PLOS	300-600 dpi	TIFF, EPS	RGB
IEEE	300+ dpi	EPS, PDF	RGB or Grayscale

Resources

Bundled Resources

References (in references/):

journals_formatting.md: Comprehensive journal formatting requirements
conferences_formatting.md: Conference paper specifications
posters_guidelines.md: Research poster design and sizing
grants_requirements.md: Grant proposal requirements by agency

Templates (in assets/):

journals/: Journal article LaTeX templates
posters/: Research poster templates
grants/: Grant proposal templates

Scripts (in scripts/):

query_template.py: Search and retrieve templates
customize_template.py: Customize with author info
validate_format.py: Check compliance with requirements

External Resources

Journal Author Guidelines:

Nature: https://www.nature.com/nature/for-authors
Science: https://www.science.org/content/page/instructions-authors
PLOS: https://plos.org/resources/for-authors/
Cell Press: https://www.cell.com/author-guidelines

Conference Formatting:

Grant Resources:

NSF PAPPG: https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg
NIH Forms: https://grants.nih.gov/grants/how-to-apply-application-guide.html
DOE Funding: https://science.osti.gov/grants

Example Usage

Example 1: Nature Article Submission

User: "I need to prepare a manuscript for Nature"

Response:
1. Load Nature formatting requirements (references/journals_formatting.md)
2. Retrieve Nature template (assets/journals/nature_article.tex)
3. Key requirements:
   - Length: ~3000 words, ~5 pages
   - Format: Single column, 12pt font
   - Citations: Numbered superscript (Nature style)
   - Figures: 300+ dpi, RGB color
4. Customize template with your title, authors, affiliations
5. Compile and validate against requirements

Example 2: NeurIPS Conference Paper

User: "What are the formatting requirements for NeurIPS?"

Response:
From references/conferences_formatting.md:
- Page limit: 8 pages main text + unlimited references/appendix
- Format: Two-column, 10pt font
- Template: neurips_2024.sty (official style file)
- Anonymization: Required for initial submission
- Citations: Numbered (brackets)
- Figures: High resolution, colorblind-safe recommended

Example 3: Conference Poster

User: "I need to create a poster for ISMB"

Response:
ISMB poster specifications:
- Size: Typically A0 portrait (33.1 × 46.8 inches)
- Recommended template: beamerposter or tikzposter
- Font sizes: Title 60-85pt, Headers 36-48pt, Body 24-32pt
- Include: QR code for paper/supplementary materials
Available templates:
- assets/posters/beamerposter_academic.tex
- assets/posters/tikzposter_research.tex

Updates and Maintenance

Template Currency:

Templates updated annually or when venues release new guidelines
Last updated: 2024
Check official venue sites for most current requirements

Reporting Issues:

Template compilation errors
Outdated formatting requirements
Missing venue templates
Incorrect specifications

Summary

The venue-templates skill provides comprehensive access to:

50+ publication venue templates across disciplines
Detailed formatting requirements for journals, conferences, posters, grants
Helper scripts for template discovery, customization, and validation
Best practices for successful academic submissions

Use this skill whenever you need venue-specific formatting guidance or templates for academic publishing.

About this skill

Automatic

Research pack

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✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

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Source

Imported

foryourhealth111-pixel / vibe-skills

bundled/skills/venue-templates/SKILL.md

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License Apache-2.0Imported 8/3/2026Version v1Bundled 7 files · scripts

Illustrative Want to see what foryourhealth111-pixel/venue-templates 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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Venue Templates

Overview

When to Use This Skill

Boundary

Core Capabilities

1. Journal Article Templates

2. Conference Paper Templates

3. Research Poster Templates

Workflow: Finding and Using Templates

Step 1: Identify Target Venue

Step 2: Query Template and Requirements

Step 3: Review Formatting Requirements

Step 4: Customize Template

Step 5: Validate Format

Step 6: Compile and Review

Template Categories

By Document Type

By Discipline

Helper Scripts

query_template.py

customize_template.py

validate_format.py

Best Practices

Template Selection

Customization

Compliance

Submission

Common Formatting Requirements

Page Limits (Typical)

Citation Styles by Venue

Figure Requirements

Resources

Bundled Resources

External Resources

Example Usage

Example 1: Nature Article Submission

Example 2: NeurIPS Conference Paper

Example 3: Conference Poster

Updates and Maintenance

Summary

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