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

Annotations already mark it read-only, open-world, and non-destructive; the description adds meaningful behavior beyond that: semantic search over plain-English text, a keyword fallback, and the specific return fields per hit. No contradiction with annotations.

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 dense sentences with no fluff: the first defines scope, the second explains mechanism and expected output. Information is front-loaded and every clause contributes.

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?

Given the simple schema and read-only annotations, the description covers everything needed to select and invoke the tool correctly: what it searches, how queries are interpreted, and what each hit returns. No output schema exists, so the explicit return-fields list is valuable and sufficient.

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?

Input schema already describes both parameters fully (100% coverage). The description adds value by clarifying that 'query' is interpreted as a plain-English semantic-search query rather than a simple keyword match, and by specifying the corpus searched.

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'), a clear resource ('open grant opportunities in the GrantSonar corpus'), and scope ('federal, state, and foundation grants'). This distinguishes it from siblings like get_grant (specific grant retrieval) and list_my_matches (personalized matches).

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?

Describes the input style ('plain-English description of the project or need') and mechanism ('semantic similarity ... with a keyword fallback'), making the intended use case clear. It does not explicitly call out when not to use it or name alternatives, but the context is sufficient.

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