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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, but the description adds substantial behavioral context: it checks eligibility criteria (stage, funding gate, raised-amount cap, etc.), ranks categories by user needs, excludes paused/closed programs, and clarifies that values are 'headline maximums, not guarantees.' This goes well beyond the annotation baseline.

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 carries information: purpose, usage, behavioral specifics, return format, and caveats. It is front-loaded with the core purpose, then proceeds logically. For a tool with 12 parameters and complex ranking logic, this length is justified and well-structured.

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?

With no output schema, the description fully accounts for the return value: up to 25 programs, each with value, qualification status and reason, how to claim, links, and a realistic total. It also covers exclusions (paused/closed) and the ranking logic. Nothing an agent needs to call it correctly is missing.

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%, so the baseline is 3. The description adds meaningful context on the 'needs' parameter (ranks the categories the user needs first and takes each need in turn) and clarifies the 'limit' behavior via the max-25 return. It doesn't add detail for every parameter, but the marginal value is clear, earning a 4.

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 states a specific verb (rank) and resource (startup perks a company can claim), enumerates providers, and explicitly differentiates from siblings by noting search_startup_perks is for lookup without a profile and get_startup_perk for one program's terms. This is a textbook example of purpose clarity.

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 explicitly states when to use this tool ('when the user describes their own startup and asks what they can get or qualify for') and names the alternatives with their distinct use cases. No ambiguity remains about which tool fits which scenario.

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