datagov_search_datasets

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

The readOnlyHint annotation already declares this as a safe read operation. The description adds useful context: the catalog size, supported query dimensions, and the return fields. It does not discuss pagination behavior, rate limits, or potential empty-result scenarios, but with the annotation covering safety, the added detail is sufficient for a basic understanding.

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 three sentences, front-loaded with the action and resource, and every sentence earns its place. Examples are integrated inline, and there is no redundant restating of the tool name or the readOnlyHint annotation.

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 search tool with six well-documented parameters and no output schema, the description covers the core purpose, filter usage, and return fields. It does not explain edge cases like pagination or facet usage, but the schema provides parameter-level details for those. Overall, it is sufficiently complete for an agent to select and invoke the tool for a typical search task.

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 individually described. The description adds value by demonstrating fq syntax with concrete examples ('organization:nasa-gov', 'res_format:CSV') and explaining the semantic categories (keyword, topic, agency, format). It also clarifies the return payload structure, which complements the schema's parameter-level descriptions.

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 uses a specific verb ('Search') and resource ('Data.gov federal open data catalog'), with clear scope ('400K+ datasets') and explicit return fields. It distinguishes itself from sibling tools like datagov_dataset_detail and list_datasets by focusing on the federal open data catalog search.

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 clearly indicates when to use the tool: to find datasets by keyword, topic, agency, or format. It provides concrete examples of fq filter usage, which helps the agent formulate effective queries. It does not explicitly name alternatives or state when not to use it, but the search purpose is clear and self-contained.

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