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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does state it is a 'read' operation, built live from USAspending.gov, and mentions a cost ($0.09 via x402). However, it does not disclose potential rate limits, failure modes, or nuances like data freshness windows beyond 'recent.' This is moderate transparency for a non-destructive read 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 description is compact and front-loaded with the core purpose, then adds cost, data source, and use case. Each sentence earns its place: the first defines the tool, the second provides provenance, the third signals intended beneficiaries. No fluff or redundancy.

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?

There is no output schema, so the description compensates by naming the return fields: top recipients, award amounts, awarding agencies, and sector activity score. It also covers context like data source and pricing. It lacks detail on edge cases or response shape, but for a search tool with three simple parameters, it is sufficiently complete.

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 67% (q and months documented, x_payment not). The description adds minimal meaning beyond the schema—it reiterates 'keyword/sector' which maps to q and implies 'recent' relates to months, but offers no additional semantics for x_payment. Since coverage is not high enough to reach baseline 4 but not low enough to require heavy compensation, a 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?

The description clearly states the tool's function: 'search recent US federal contract awards by keyword/sector and get the top recipients, award amounts, awarding agencies, and a sector activity score.' It also explicitly ties it to USAspending.gov, distinguishing it from sibling tools like eu_tender_intelligence. This is a specific verb+resource+output description that fully differentiates it in the tool ecosystem.

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 provides clear intended usage: 'The market-intelligence read sales, research, competitive-intel and prospecting agents make to see who's winning government money in a space.' This gives context on when to use the tool but stops short of explicitly stating exclusions or naming alternative tools. It is clear enough for an agent to understand its niche without explicit 'when-not-to-use' guidance.

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