get_census_metric_detail

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

With no annotations, the description carries the transparency burden. It clearly indicates this is a read-only metadata lookup and adds context about public-domain data. It doesn't fully disclose possible failure modes or rate limits, but for a metadata retrieval tool this is adequate.

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?

Three compact sentences: purpose, usage context, and parameter/source info. No filler, front-loaded with the most important information, and each 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?

Despite minimal schema and no annotations, the description covers the tool's purpose, input semantics, output contents, and data source. With a single parameter and an output schema available, this is complete 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?

The schema gives no description for the 'metric' parameter, but the description explains it is the canonical_name and gives an example ('median_household_income'). This fully compensates for the 0% schema coverage and clarifies the expected value format.

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 gets metadata for a single US Census metric, including source variables and margin-of-error formula type. It uses a specific verb and resource, and the phrase 'single metric' differentiates it from comparison tools like compare_census_metric.

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?

Explicitly says 'Use this after explore_census_metrics to understand exactly what a metric measures,' providing a clear workflow placement. This tells the agent when to invoke this tool relative to siblings.

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