explore_census_metrics

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

With no annotations, the description carries the behavioral disclosure burden. It reveals a 50-result cap, case-insensitive filters, and substring match behavior on query. It does not mention pagination or error handling, but for a read-only discovery tool this is reasonable. The description adds value beyond the schema by specifying match semantics and result limits.

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 organized: purpose, usage guidance, parameter details, result limit, and source. Each sentence delivers distinct information without redundancy, and the most critical usage guidance is front-loaded.

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 two-parameter tool with an output schema, the description covers what the schema does not: workflow placement, search behavior, and result cap. It is sufficient for an agent to select and invoke 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 0%, so the description fully compensates. Query is defined as 'substring match on display_name or canonical_name', and category is illustrated with concrete examples ('demographics', 'economy', 'housing'). Case-insensitivity is also documented, which is not present in the schema.

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 identifies the tool as a discovery endpoint for US Census Bureau metrics, with the specific verb 'Discover'. It explicitly differentiates from sibling tools by stating its role: 'Use this to find the canonical_name of a metric before calling the place or breakdown tools.'

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?

It explicitly states when to use this tool versus alternatives: 'Use this to find the canonical_name of a metric before calling the place or breakdown tools.' It also distinguishes from BLS tools by mentioning 'US Census Bureau data', giving implicit selection criteria.

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