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

Annotations already declare readOnlyHint/openWorldHint, so the bar is lower, and the description adds genuine semantic context: what a 'terms-aggregation count' means and how revenue_band buckets the data. It does not discuss pagination or how the facet counts are returned, but that is largely covered by the output schema.

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?

Front-loaded with the core purpose, then the facet enum and bucket explanation. It is a bit long and repeats form_filed and has_financials phrasing that already appears in the schema, but every sentence is largely informative.

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 an output schema exists and annotations cover safety, the description supplies enough to call the tool correctly: required facet, allowed facet values, filter scoping, and the sibling to use instead. Remaining details like pagination are handled by the structured fields.

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% and the schema already documents all 20 parameters, so the baseline is 3. The description adds some value by enumerating the facet values and expanding the revenue_band bucket labels, but it mostly restates what the schema already provides for form_filed and has_financials.

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?

It states a specific verb+resource: 'Returns terms-aggregation counts for one facet of the SEC companies dataset'. It explicitly distinguishes itself from the sibling search tool by noting it is scoped to the same filters as search but returns aggregation counts rather than results.

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 final sentence routes the agent to datasets_sec_companies_search for actual searching, and 'scoped to the same filters as search' clarifies the relationship between the two. However, it never states explicitly when a caller should prefer facet counts over a search, leaving that inference to the agent.

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