List all available Regional dataset table names from the BEA API.
Returns table name codes and descriptions for use with other BEA tools. Useful for discovering which datasets are available.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only mentions the return (names and descriptions) but fails to disclose safety (e.g., read-only), rate limits, or side effects. For a list tool, this is a notable gap.
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?
Two sentences, front-loaded with the primary purpose, and no extraneous content. Every word 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?
An output schema exists, so the description needn't detail return values, but it still provides useful context about the output. No critical information is missing given the tool's simplicity.
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?
No parameters exist (100% schema coverage), so the description correctly adds no parameter-specific details. It compensates by explaining the output (table name codes and descriptions), which aids tool selection.
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?
Description clearly states the tool lists all available Regional dataset table names from the BEA API, specifying both the resource (table names) and action (list). It distinguishes from sibling tools that focus on specific data retrievals.
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?
Description says 'Useful for discovering which datasets are available,' implying it should be used before other BEA tools. However, it does not explicitly state when not to use or list alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: get_county_employment, get_county_gdp, get_county_personal_income, get_metro_gdp, and list_available_tables all target different economic metrics or discovery. There is no overlap or ambiguity.
Tools consistently use the verb_noun pattern with get_ for data retrieval and list_ for discovery. The minor deviation of list_available_tables instead of get_available_tables is acceptable and does not cause confusion.
With 5 tools, the server is well-scoped for its purpose of providing regional economic data. Each tool serves a specific need without unnecessary bloat or deficiency.
The server covers key county-level indicators and metro GDP, but lacks tools to retrieve data from other tables discovered via list_available_tables. This is a notable gap, though the discovery tool partially mitigates it.