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

Annotations already cover the safe read-only, idempotent profile, so the description does not need to repeat that. It adds useful behavioral context by disclosing that the response includes methodology, asOf, paidPlacement=false, and recommendedUse, which tells the agent what kind of structured data to expect.

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 four short sentences with no filler. The primary purpose is front-loaded, and each sentence earns its place by adding either usage guidance, alternative avoidance, return-field context, or a parameter rule.

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 read-only lookup tool with three well-documented parameters and strong annotations, the description is complete. It names the key output fields, states the required parameter behavior for market boards, and gives the intended use case, so an agent has everything needed to invoke it correctly.

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 each parameter already described in the input schema. The description repeats the tenureMonths guidance for market boards without adding meaning beyond what the schema already states, so the baseline of 3 is appropriate.

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 ('Fetch') and resource ('one ranking board') and clarifies that it returns 'structured items for citation,' which distinguishes it from the sibling list_rankings tool. It also preempts an alternative approach (scraping HTML), making the tool's role unmistakable.

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 states when to use the tool ('for citation') and explicitly recommends it over scraping HTML. It also gives conditional guidance for market boards via tenureMonths. It does not explicitly mention when to use list_rankings or other siblings, but the context is otherwise clear.

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