vision_get_setup_guide

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states that the tool will not automatically select or enable any models, which is a useful non-mutation guarantee. However, it does not disclose return format, whether it is purely read-only beyond the stated behavior, or any other limitations.

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 exactly two sentences, front-loaded with the primary purpose and followed by a brief non-action statement. Every word earns its place; no filler or redundancy.

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 simple tool with no parameters, no output schema, and no annotations, the description is complete. It states what the tool returns, what it does not do, and is adequate for an agent to understand its function and side-effect profile.

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?

The tool has zero parameters, so the schema description coverage is trivially 100%. Per guidelines, a 0-parameter tool receives a baseline of 4. The description adds no parameter semantics because none exist.

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 returns visual model configuration instructions and recommended suppliers. This specific verb-resource pairing ('returns... instructions') differentiates it from siblings like vision_list_models (lists models), vision_analyze (analyzes), and vision_test_connection (tests connections).

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?

The description provides clear context: use this tool when you need configuration instructions and supplier recommendations. The explicit 'will not automatically select or enable any models' implies it is a reference guide, but it does not explicitly name alternative tools or provide when-not-to-use conditions, so it stops short of a 5.

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