datasets_sec_institutional_positions_facets

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states that the tool returns terms-aggregation counts, indicating a read-only operation, but does not disclose any pagination, limits, authentication requirements, or other behaviors. It is transparent about the output nature but lacks details on potential side effects or constraints.

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 front-loaded: it states the purpose, the output type, the scoping to search filters, and the facet enum in just three sentences. Every sentence adds essential information without redundancy. This is an ideal level of conciseness for a tool of this complexity.

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 faceting tool, the description is sufficiently complete. It explains what the tool does, what it returns (terms-aggregation counts), and the valid facet values. The scoping to search filters is mentioned. While it does not detail response format or limits, the absence of an output schema and the straightforward nature of the tool make this adequate.

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 provides 100% coverage for all parameters, so the description adds little beyond what the schema already states. It mentions 'scoped to the same filters as search', which gives context that the filter parameters (cusip, issuer_name, manager_cik) are consistent with the search tool, but does not add new semantics. This meets the baseline for fully-documented parameters.

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 facets the SEC institutional positions dataset and returns terms-aggregation counts for a specified facet, listing the facet enum values. It distinguishes itself from search by noting it is scoped to the same filters as search, though it does not explicitly name the sibling search tool. The purpose is clear and specific, but lacks an explicit sibling differentiation.

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 this tool is for obtaining facet counts rather than records, but it does not explicitly state when to use it versus the search tool. The phrase 'scoped to the same filters as search' gives context that it applies the same filters but does not explicitly guide on choosing between faceting and search. Usage guidance is implied rather than explicit.

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