facets

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

With no annotations, the description carries full behavioral burden. It does disclose the specific facets and rates computed, which is useful. However, it omits any details about how counts are aggregated, whether the tool is read-only, performance characteristics, or the meaning of 'rates'. The description adds some context beyond the name but is far from transparent.

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 a single, compact sentence that front-loads the core purpose and enumerates key facet dimensions. There is no filler or redundant phrasing. It is concise and well-structured for quick parsing.

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?

Although an output schema exists (which may explain return values), the description remains incomplete for a tool with four optional parameters and no annotations. It covers what the tool computes but not how to control the computation via parameters, when to use it, or what contexts it serves. The gap in parameter semantics alone makes this insufficient for confident invocation.

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 has 4 parameters with zero description coverage, and the tool description does not mention any of them. There is no explanation of top_n, prefix, client_id, or max_records. For a tool with no required parameters and an otherwise generic schema, the description fails to compensate, leaving the agent without clues about how to constrain the facet results.

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 providing facet counts for types, years, publishers, languages, and clients, plus ORCID/funder/license rates. This is a specific resource and set of outputs, though it lacks a verb like 'returns' and does not explicitly differentiate from sibling tools like top_subjects or index_summary beyond the listed dimensions.

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 provided on when to use this tool versus alternatives. The description merely lists outputs, with no mention of conflicting tools, prerequisites, or exclusion scenarios. There is no indication of what types of queries or analysis would benefit from facet counts.

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