get_census_place_metric_series

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the series behavior, optional dataset, and source, but does not detail response format or error conditions. That said, the presence of an output schema means return values are already documented, so the description adds adequate value for a simple read operation.

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: first sentence states the purpose, second explains the key behavioral variation, third defines parameters and source. No wasted words; information is front-loaded and easy to scan.

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?

The description covers all essential aspects for correct invocation: what the tool does, how to control the series length, what each parameter means, and the data source. It does not mention how to discover valid metric names, but this is implicitly handled by sibling tools such as explore_census_metrics, and the output schema defines the return structure.

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 has 0% parameter descriptions, so the description must compensate. It does so effectively: 'fips is the place's FIPS code; metric is the canonical_name; dataset is optional ('acs1' or 'acs5')' and the year behavior is explained. Every parameter is given meaning beyond the raw 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 states the tool's specific function: 'Get a time series for one US Census metric in one place.' This includes a specific verb (Get), resource (time series for a metric), and scope (one place). It distinguishes from sibling tools like compare_census_metric or get_census_place_metrics by focusing on a single metric and single place.

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 context on how to use the tool: 'Omit year for the full series; provide year for a single observation.' It also explains parameter roles and optional dataset values. However, it does not explicitly mention when to use alternative tools or when not to use this one, though the purpose statement implies differentiation from siblings.

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