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

Adds substantive context beyond the annotations: results are company-provided rather than CC BY, each row carries provided_by/last_confirmed_at/sponsored, and sponsorship explicitly never affects ordering (a trust-relevant disclosure). It also warns that unknown arguments are rejected, which is a behavioral constraint not visible in the schema.

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?

Front-loads purpose and result-metadata facts before the argument list, with no filler sentences. It is dense but every clause carries information an agent needs; slightly packed, but not padded.

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?

No output schema exists, and the description compensates by naming the key result fields (provided_by, last_confirmed_at, sponsored) and the pagination contract via cursor/next_cursor. With all 8 parameters schema-documented, an agent has enough to call it correctly, though the full result shape remains unspecified.

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 the baseline is 3, and the description goes beyond it by specifying that q matches against name and short description and that query is an alias with q taking precedence. That adds real meaning about matching behavior and parameter conflict resolution.

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 (search) and resource (fintech products) and enumerates the facets it searches over: text, category, market, API availability, customer type. This clearly distinguishes it from siblings like get_product (single-product lookup) and search_organizations/search_people.

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?

Gives concrete operating conditions: use q/query for text search, omit q for a plain alphabetical listing, and pass cursor for the next page. However, it never names the alternative tools (e.g. get_product for a known product) or states when this tool is the wrong choice, so routing guidance is implied rather than explicit.

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