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

Annotations already provide readOnlyHint=true, covering the safety profile. The description adds useful context about supporting conversation history via the messages array and supporting multiple AI providers, but it does not disclose external API dependencies, rate limits, or response structure in detail. There is no contradiction with annotations.

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?

The description is three short sentences, front-loaded with the primary action. Each sentence adds value: model variety, return value, and conversation history. There is no redundant or wasteful wording.

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 tool with 3 parameters and no output schema, the description covers the essential aspects: purpose, supported models, return value, and conversation history. While a more detailed response format would be beneficial, the description is adequate for a chat tool and is supported by clear annotations.

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 100% with well-described parameters (model, messages, max_tokens). The description reiterates and reinforces the messages parameter by mentioning conversation history, but it does not add significant format or syntax details beyond the schema.

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 states a specific verb+resource combination: 'Send a message' to '30+ AI models', which clearly distinguishes it from sibling tools like ai_embeddings, ai_images, ai_speech, and ai_transcribe. It also mentions conversation history, making the chat-focused purpose unambiguous.

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?

Usage is implied through the description (message-based chat interaction), but there are no explicit when-to-use or when-not-to-use guidelines. The sibling tool names suggest different modalities, yet the description does not explicitly say 'use this for chat rather than embeddings/images'.

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