nc_linc_query

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

The readOnlyHint annotation already signals the safe read-only nature. The description adds the prerequisite workflow (use search first) and scope (specific NC LINC datasets) but does not elaborate on behavior like pagination, return formats, or how filters affect results. It does not contradict 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 concise and well-structured: a clear purpose statement, a directive for prerequisite usage, and practical examples. No superfluous words or repetition of schema details.

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?

For a simple query tool with read-only annotations and fully described parameters, the description covers purpose, workflow, and examples. It lacks explicit return format details, but since no output schema exists and the tool is straightforward, this is a minor gap. Overall, it is sufficient for correct invocation.

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%, so parameters are well documented. The description adds value by listing common dataset ID examples, which assists the dataset_id parameter. This goes slightly beyond the schema's generic description.

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 queries a specific NC LINC dataset with optional filters, and explicitly distinguishes from the sibling nc_linc_search by directing users to search first. It also provides concrete examples of common dataset IDs, making its resource scope unambiguous.

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 instructs users to use nc_linc_search first to obtain dataset IDs, establishing the appropriate workflow. It does not explicitly state when not to use this tool versus alternatives, but the dataset-specific naming and examples clearly define its context.

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