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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety profile is covered. The description adds meaningful behavioral context: it requires the user's own API key (BYOK), returns latency stats, and supports a customizable threshold. It does not mention rate limits or costs, but given annotation coverage, the added detail is valuable and non-contradictory.

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 sentences, front-loaded with the core purpose, and every sentence adds value: what it does, returns, assertion details, and BYOK requirement. No redundant or filler content; highly efficient.

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?

Given the tool's complexity (8 params, output schema exists) and 100% schema coverage, the description fully covers the workflow: input (image + test cases), supported models, assertion types, and the BYOK requirement. The output schema handles return value details, so no gap exists.

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 all 8 parameters, so the baseline is 3. The description repeats some parameter details (assertion types, image URL/base64, model names) but does not add meaning beyond the schema. It provides a concise summary but relies on the schema for full parameter understanding.

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 identifies the tool's function: running a test suite against a VLM with image and test cases. It uses a specific verb+resource ('Run a test suite against a Vision-Language Model') and lists supported models. However, it does not explicitly differentiate from the sibling tool run_vlm_test_suite_batch, so it stops short of full sibling distinction.

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 for when to use the tool — when you need to evaluate a VLM with custom test cases and assertions. It does not explicitly mention alternatives or exclusions, but the scenario is sufficiently defined to guide selection. No misleading guidance is present.

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