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

Beyond annotations, the description reveals meaningful behavior: exact-name matching for providers/programs, topic expansion via category and rare-word weighting, exclusion of paused/closed applications, and a return summary including 'stated value, the primary eligibility gate and links, plus a page to browse more.' This adds substantial context that the readOnly and idempotent annotations do not provide.

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 dense but every sentence earns its place: purpose and examples first, followed by the sibling distinction, matching behavior, exclusions, return details, and safety. It is front-loaded with the primary verb and resource, and the length is justified by the tool's breadth.

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?

Despite having no output schema, the description tells the agent what to expect in the result set. Combined with the fully documented input schema and annotations covering read-only and idempotent behavior, an agent has enough information to select and invoke this tool correctly across its six optional parameters.

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 strong. The description adds meaning beyond the schema by explaining how query semantics work ('A provider or program name returns only programs that carry that name; a topic ... also matches the category that covers it') and by clarifying the intent of open_to_any_startup ('programs open to any startup without investor or accelerator backing').

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 opens with a specific verb and resource: 'Search the catalog of 1,000+ startup programs by provider, program or topic.' It gives concrete example queries and explicitly distinguishes this tool from find_startup_perks, so an agent can tell them apart without opening either schema.

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?

It states when to use this tool ('Use it for questions like...') and when not to ('use find_startup_perks instead when the user wants what a specific company qualifies for'). It also lists the browsing modes: category, benefit type, and open-to-any-startup programs, leaving no ambiguity about the selection criteria.

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