macro_usa_cftc_nc_holding

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

Annotations already declare the tool as read-only, idempotent, and non-destructive, so the description does not need to restate that. It adds useful context by mentioning the data range, return type, and source URL, but does not disclose any subtle behaviors like rate limits or data quirks. No contradictions 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 (two lines) but contains redundancy: the first sentence and the return-type line repeat the same report name. It is front-loaded with the core information, but could be more streamlined by merging the redundant parts.

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 no-parameter data retrieval tool with annotations, the description provides the essential context: data range, source URL, and return type. However, it lacks detail on the actual columns or contents of the DataFrame (e.g., fields like currency, open interest, positions), which could be important for an agent selecting this tool. Given the absence of an output schema, this is a notable gap.

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 tool has zero parameters, so the description need not elaborate on parameter semantics. The schema is empty, and the description provides no additional parameter context, which is acceptable given there are none to describe.

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 identifies the tool as a CFTC foreign exchange non-commercial holdings report, specifying the data range (19830107-present) and source URL. This distinguishes it from sibling tools like macro_usa_cftc_c_holding or merchant_currency_holding, which cover different report categories.

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 implies usage by stating what data it returns (a pandas DataFrame of CFTC FX non-commercial holdings), but provides no explicit guidance on when to use this tool versus alternatives or any exclusions. The context is sufficient for an agent to infer its use, but not explicitly stated.

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