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

Annotations already cover readOnly, idempotent, openWorld and non-destructive, and the description adds meaningful context beyond them: the underlying dataset, the case-insensitive substring matching behavior, and the dimensions of the aggregation. It does not describe pagination or result size limits, but the added disclosure is solid for a read-only aggregation tool.

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 core action and data source are front-loaded, and each sentence adds information (source, output dimensions, matching behavior, usage, scope caveat). It is somewhat dense but no sentence is pure filler.

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 carries the burden of describing returns and does so explicitly: total dollars sold, number of purchase records, and breakdowns by agency, DIR contract, and fiscal year. Combined with the data-source and matching notes, an agent has everything needed to call it correctly.

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 both parameters are already documented in the schema, including the case-insensitive substring semantics for vendor and the fiscal_year example. The description largely repeats the schema's substring-matching note rather than adding new meaning, so the baseline 3 applies.

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 (aggregate) and resource (a vendor's Texas state cooperative-contract sales), names the exact data source (DIR Vendor Sales Report on data.texas.gov), and enumerates the output breakdowns. An agent can distinguish it from tx_procurement_awards because it is scoped to a single vendor rather than awards generally.

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?

"Use this to size up a single vendor's business with the State of Texas" gives clear when-to-use context, and "This is TEXAS STATE data (not federal)" scopes it away from federal tools. It does not explicitly name the sibling tx_procurement_awards or state when-not to use this tool, keeping it short of a 5.

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