Venice Chat (LLM)

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

With no annotations provided, the description carries full burden. It discloses key behaviors: uncensored nature (NSFW allowed where model permits), auth methods (x402 wallet, API key), context limits (524K, 1M reachable), and model catalog scope. For a chat tool with no annotations, this is substantive disclosure of safety/staleness/auth traits.

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

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

Dense but efficient single paragraph. Provides operator preferences as a compact shorthand. Somewhat packed (the 'cheap+long → 1M ctx → character voice → premium reasoning' chain is telegraphic but informative). No wasted words, though it could be structured with clearer separators.

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

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

For a 6-param no-output-schema tool, the description covers model selection, auth, uncensored policy, and context limits. The main gap is undocumented sampling parameters (stop, top_p, temperature, max_tokens are barely semantic), and no mention of what the response contains. Handles the catalog/scale complexity well.

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

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

Schema coverage is only 33% (messages and model have descriptions), so the description partially compensates by mentioning model selection guidance. However, it adds nothing about stop, top_p, max_tokens, or temperature beyond what's in the schema (which documents messages and model only). The other 4 params are undocumented in both schema and description, creating a coverage gap.

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

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

The description clearly states the tool runs an OpenAI-compatible chat completion via Venice's LLM catalog, naming specific models. It's distinct from venice_responses and venice_chat_with_character because it's the raw LLM chat endpoint rather than character-based. Could be slightly better at explicitly contrasting with venice_responses, but the verb+resource+scope is clear.

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

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

Provides concrete guidance: default model selection, alternative models to try, context-length escalation ladder (cheap+long -> 1M ctx -> character voice -> premium reasoning), and NSFW allowance. Names alternatives (qwen-3-7-max, venice-uncensored-role-play, gemini-3-1-pro-preview). Doesn't explicitly say when NOT to use it vs venice_chat_with_character or venice_responses, which is a minor gap.

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