nsf_get_award

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

The description extensively discloses behavior beyond annotations: non-existent id returns found:false, never fabricated records; type handling of monetary fields; error conditions like serviceNotification and schema drift. This adds significant value over the readOnlyHint and openWorldHint annotations.

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 lengthy and includes many verbose details (e.g., about NSF award nature, type conversions). Although each piece adds value, the overall length could be reduced for better conciseness without losing essential 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 the simple tool and lack of output schema, the description fully covers input, expected behavior, error cases, and return shape. It addresses all necessary aspects for an AI agent to use the tool 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 coverage is 100%, and the description reinforces the schema's description of awardId with additional details on digit length and validation. While not entirely new, it provides helpful elaboration that aids correct usage.

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 'Fetch ONE NSF award by its numeric award id', specifying the exact resource and action. It distinguishes itself from sibling 'nsf_search_awards' by emphasizing 'ONE' and the specific numeric id format.

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 usage context, including input validation (all-digit, 5-9 digits) and the data nature (research grants vs. contracts). However, it lacks explicit guidance on when not to use this tool or direct alternatives among siblings.

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