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

Annotations already establish that the tool is read-only, idempotent, and non-destructive. The description adds value by disclosing the output fields (total, male, female, median age) and the full range of geography levels, which is useful because no output schema exists. It does not reveal data-source nuances beyond the schema's year parameter, but the annotations lower the burden.

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 focused sentences: action and scope, return values, and use cases. There is no filler, repetition, or buried detail, and the most important identifying information 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?

Given the tool's complexity — 8 parameters, level-dependent requirements, no output schema — the description plus the fully covered schema is sufficient for an agent to select and invoke it correctly. It explains the core return payload and application context, while the schema handles parameter formats and prerequisites.

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 description coverage is 100%, and the schema itself documents every parameter, including conditional requirements like 'Required for msa level' and valid enum values. The description's geography list is useful but largely repeats what 'level' already conveys, so it adds little semantic value beyond 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 begins with a specific verb and object — 'Get total population for a US geography' — and enumerates the supported geography types and exact outputs. It does not explicitly contrast with sibling tools like census_demographics, but the narrow focus on population, sex, and median age makes the purpose reasonably distinct.

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 gives concrete application contexts: 'market sizing, location intelligence, demographic analysis.' However, it does not state when to prefer this tool over the many adjacent census_* siblings or mention exclusions, so an agent must infer routing from tool names and scope.

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