search_faceted

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

With no annotations, the description carries the full burden of behavioral disclosure. 'to get aggregations/counts' usefully hints at the return shape (count data rather than result lists), but it discloses nothing about pagination, permissions, whether hits accompany the aggregations, or how facets map to response buckets.

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?

One sentence with a front-loaded verb and zero filler—every word earns its place. It is efficient, though brief enough to edge toward under-specification rather than genuine conciseness.

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?

With no output schema and no annotations, this is thin coverage for a 3-parameter tool. An agent cannot determine what the response contains (only counts, or hits too?), how doc_types alters the search scope, or how this differs operationally from the five other search siblings. The high-calibration example shows this level of tool can be fully covered in two sentences.

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 description coverage is 67% (query and facets documented; doc_types only via its enum values), so the schema already does most of the parameter work. The description adds only the 'aggregations/counts' purpose, which contextualizes facets but doesn't clarify how doc_types changes scope or how the query string behaves. This sits at the baseline.

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 states a specific verb and resource ('Perform a faceted search') and adds the operational purpose ('get aggregations/counts'), which sets it apart in kind from siblings like search_assets and search_by_date_range. However, it never names the search domain (assets/collections), leaving the doc_types parameter to carry that meaning alone.

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?

No guidance is given on when to choose faceted search over the many search siblings (search_assets, search_by_metadata, search_by_date_range, search_segments). An agent receives no selection conditions, exclusions, or hints about which tool fits which query scenario, so it must infer usage from the name alone.

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