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

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context beyond this: it sums 'obligated dollars plus unexercised ceiling' and excludes smaller/unlisted recipients, disclosing how the ranking is computed. This enriches the agent's understanding of the operation, though it doesn't explain the 'resolve to a listed company' mapping in depth.

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 four sentences, front-loaded with the primary purpose, followed by essential methodology and a usage example. There is no redundant filler, and each sentence adds value, though it could be tightened slightly without losing information.

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 no output schema, the description explains the tool's scope and ranking logic but does not explicitly state the return fields (e.g., company name, ticker, total amount). It covers the main use cases and limitations reasonably well, making it mostly complete for an agent to select and invoke the tool.

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 coverage is 100%, with each parameter (endDate, startDate, maxResults) already described clearly. The description references the date range and 'largest first' ordering, but it does not add new semantic meaning beyond what the schema provides. Baseline 3 is appropriate because the schema does the heavy lifting.

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 ranks public companies by total federal contract dollars over a date range, explicitly naming the data source (USAspending.gov), the inclusion threshold ($1M+ prime awards), and the exclusion criteria. It distinguishes itself from the sibling tool GetGovernmentContracts by directing users to that tool for individual company awards.

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 provides an explicit example question ('which public companies won the most federal contracts last quarter') and gives an alternative tool with the line 'Use GetGovernmentContracts for one company's individual awards.' This gives clear when-to-use and when-not-to-use guidance, exceeding what is typically seen.

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