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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is covered. The description adds useful behavioral context: results default to dollar-amount ranking and it enumerates the fields each record returns, which helps an agent interpret output even without an output schema.

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?

Front-loaded with the core purpose and data source, followed by result fields, filters, ranking default, and disambiguation. The three illustrative questions are slightly listy but each earns its place by grounding the use case. Reasonably sized for a nine-parameter tool.

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 compensates by enumerating the returned fields (customer, vendor, amount, contract number, RFO description, brand, quantity, dates) and the filter dimensions, and it disambiguates the data source. Nothing an agent needs to call this correctly appears 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 all nine parameters are already documented with examples. The description restates the filter set (vendor, agency, keyword, fiscal year, contract number, min amount) and the default sort, but adds no syntax or constraint detail beyond what the schema already provides. Baseline 3 is appropriate.

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) and resource (Texas state government contract awards & purchases) and pins the data source (Texas DIR Cooperative Contract Sales on data.texas.gov). It defines the result granularity (each result is a purchase against a DIR cooperative contract) and disambiguates from federal data, though it never names the closest sibling tx_procurement_vendor explicitly, so award-level vs vendor-level differentiation is only implied.

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?

Gives concrete usage context with example questions ("who won Texas state IT contracts", "biggest vendors to the Texas Health and Human Services Commission"). It states the domain clearly (Texas STATE, not federal) but offers no explicit when-not or pointer to an alternative tool such as tx_procurement_vendor for aggregated views.

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