bea_fixed_assets

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

Annotations already declare readOnlyHint=true, so the safe-read nature is covered. The description adds useful behavioral context by disclosing update frequency and the annual nature of the data, which helps set expectations. No contradiction with annotations.

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. It leads with the primary purpose, then provides scope details and common table names in three short paragraphs. Every sentence is informative, with no fluff or repetition.

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 data retrieval tool with no output schema and no nested objects, the description covers all relevant aspects: what data is included, update schedule, example tables, and how to discover more. 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 100%, so the baseline is 3. The description adds value beyond the schema by naming common table examples (FAAt101, FAAt201, FAAt401, FAAt801) and indicating that table_name defaults to FAAt101, giving users concrete starting points.

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 specifies the tool's function: 'Get Fixed Assets data — net stock, depreciation, and investment tables.' It names specific categories (private/government fixed assets, equipment, structures, IP products) and distinguishes it from sibling BEA tools by focusing on the FixedAssets dataset, listing common table names.

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 usage context: 'Annual data only, updated once per year (late August – early October)' and directs users to 'Use bea_dataset_info to discover all table names.' It doesn't explicitly state when not to use this tool relative to other BEA datasets, but the scope is clear enough.

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