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

Annotations cover readOnlyHint, but the description adds a critical behavioral fact they do not: the credit cost model (1 credit per record, minimum 2). That is valuable and non-obvious. It doesn't mention rate limits or whether results are cached, so it falls short of a 5.

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 tight sentences with no filler, and the most decision-relevant facts (cost, alternative tools) are front-loaded. No structural issues.

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?

Covers the scope of the search, the cost implication, and the alternative tools, which is strong for a 26-parameter search tool. It stops short of explaining pagination limits or what the output schema returns, but the output schema exists and the annotations handle safety.

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%, so every parameter is already documented in the schema. The description only calls out page_size as a cost lever, which is meaningful but limited given the schema does the rest.

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?

States a specific verb and resource ('Search stored TrustMRR startup records') and enumerates the distinguishing data fields (payment-provider-verified revenue and MRR plus traffic, growth, and category). This clearly separates it from trustmrr_leaderboard and datasets_trustmrr_facets.

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?

Explicitly routes the agent: use datasets_trustmrr_facets to inspect filter counts, or trustmrr_leaderboard for the ranked list. It also gives a concrete cost-control rule ('keep page_size to what you need'), which is actionable when-to-use guidance.

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