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

Annotations already declare readOnly, idempotent, and non-destructive. The description adds valuable context: it returns matching IDs and names, orders by best match first, and supports partial names. This goes beyond what annotations provide.

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?

Two concise sentences with the primary purpose front-loaded and no filler. Examples are embedded naturally.

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?

Since there is no output schema, the description appropriately states what is returned (IDs and names, best match first). It omits edge-case handling (e.g., no results) but is sufficient for a typical lookup scenario.

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% for the single query parameter. The description adds examples and clarifies partial matching, which is helpful but only a modest enhancement over the schema's 'Model name or part of it'.

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 uses a specific verb ('Find') and names the resource ('exact id of an LLM tracked by InferIndex'), with concrete examples. It clearly distinguishes this lookup tool from cost-focused siblings like cheapest and estimate_cost.

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 for retrieving model IDs from names, but there are no explicit alternatives or when-not-to-use conditions. The tool's purpose makes the context clear, but it does not state exclusions or trade-offs versus sibling tools.

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