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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds valuable behavior beyond that: case-insensitive substring matching, name-variant surfacing, and the specific aggregation logic. No contradictions 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?

Three sentences, each earning its place: the main aggregation purpose, the matching behavior with an example, and the usage/scope guardrail. No redundant wording, and the most important information is front-loaded.

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?

For a read-only, two-parameter aggregation tool with no output schema, the description is complete. It specifies the return composition (dollar totals, contract counts, breakdowns), the matching rule, and the geographic scope. Nothing an agent needs for correct invocation 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% and the schema descriptions for both parameters are already informative. The tool description reiterates the substring behavior but adds no new parameter-level semantics; per calibration, a baseline of 3 is appropriate when the schema handles parameter meaning.

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 clearly states the tool aggregates a vendor's New York State contract awards from a specific data source, enumerating the exact outputs (total dollars, number of contracts, breakdowns). It also explicitly distinguishes its scope from federal and NYC data, and the sibling ny_procurement_awards is implicitly differentiated by the aggregation focus.

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?

The description gives an explicit use case ('size up a single vendor's business with New York State authorities') and clarifies the geographic scope to prevent misuse. It does not name an alternative tool outright or provide exclusions, but the context is clear enough for correct selection.

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