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

Annotations already flag readOnlyHint=false and destructiveHint=false, so the description doesn't need to rehash safety. The description adds useful behavioral context: parallel execution across models, returning each answer for comparison, and that the user's model stays in charge. It does not disclose potential side-effects such as the share option creating a public page, though the schema does. Given the annotation coverage, this is adequate but not rich.

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 two sentences, front-loaded with the core action, followed by concrete use cases and a reassurance about provider switching. Every word earns its place with no redundancy or filler.

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?

The description covers the tool's function, use cases, and basic behavior, which is sufficient for an agent to decide when to invoke it. The schema and output schema handle parameter details and return structure. It omits the conditional sharing/publication side-effect and cost/time implications, but these are either in the schema or not essential for selection. It is nearly complete for a tool of this complexity.

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 description coverage is 100%, and the schema itself provides detailed explanations for parameters (e.g., share's public-link behavior, max_tokens being kept low, perspectives as role labels). The tool description does not need to repeat parameter semantics, thus the baseline of 3 applies. It adds no extra meaning beyond the schema but also doesn't create ambiguity.

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 a specific action: 'Get a SECOND OPINION: run one prompt across Gonka models in parallel and return each answer for comparison.' It distinguishes itself from siblings like gonka_chat by emphasizing multi-model parallel execution and comparison, and clarifies the user's own model remains in charge. The purpose is unambiguous and resource-specific.

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 gives explicit use cases: 'sanity-check a decision, test a hypothesis, or see where other models/viewpoints agree or differ.' It also notes the benefit 'without switching your main provider.' However, it does not explicitly state when NOT to use this tool or name alternative tools, so it falls shy of a 5.

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