analyze_award_patterns

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. Description adds value by stating data source (USAspending + FPDS) and cost (3 credits), which are beyond the annotations and provide useful behavioral context.

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?

Two sentences front-load the purpose and outputs, then state data source and cost. No filler or redundancy; every sentence earns its place.

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 complexity (4 params, output schema exists), description covers purpose, outputs, data source, and cost. Could mention data recency or limitations, but overall sufficient.

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?

Input schema provides full descriptions for all 4 parameters (100% coverage). Description does not add parameter-specific semantics beyond the schema, so baseline score of 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?

Description clearly states the tool analyzes award patterns for contracts in a NAICS, listing specific outputs (award-size distribution, competition mix, etc.). It distinguishes from siblings like analyze_market by narrowing to award patterns and listing typical metrics.

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?

Description implies use when award pattern analysis is needed, but does not explicitly state when to use or avoid this tool versus siblings like analyze_market or find_incumbents. No alternative guidance provided.

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