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venice_chat

Send user messages to Venice AI and receive LLM-generated responses. Supports model selection, token limits, temperature, and system prompts.

Instructions

Send a message to Venice AI and get a response from an LLM

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoModel ID (e.g., llama-3.3-70b, deepseek-r1-llama-70b)llama-3.3-70b
messageYesThe user message to send
max_tokensNoMaximum tokens to generate
temperatureNoSampling temperature (0-2)
system_promptNoOptional system prompt
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, and the description only states basic functionality without disclosing behavioral traits such as statelessness, rate limits, or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no superfluous words, but it could be structured to include more helpful context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 parameters, no output schema), the description is minimally adequate but lacks explanation of overall behavior, such as the stateless nature of requests.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents parameters. The description adds no additional meaning beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action 'send a message' and resource 'Venice AI get a response from an LLM', which is distinct from sibling tools like image generation or text-to-speech.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, nor any context about when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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