openalex_aggregate_works

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

With no annotations, the description carries full burden. It discloses the return format (list of {key, label, count} groups sorted descending) and mentions combining with filters. It lacks details on rate limits, authentication, or potential performance issues, but covers core behavior well.

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 only 3 sentences, front-loaded with the core action, and each sentence adds value. No unnecessary information or repetition.

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?

The tool has 3 parameters and no output schema. The description explains return format and usage, but lacks detailed parameter constraints, especially for group_by valid values. The cross-reference to another tool's syntax helps but is not fully self-contained, leaving gaps for an AI agent.

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?

Given 0% schema coverage, the description must compensate. It mentions group_by but does not explain valid values (e.g., field names). Query and filters are described only by cross-reference to another tool's syntax, which is helpful but not self-contained. The schema provides no further clues, so some ambiguity remains.

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 aggregates works by a field to get distribution statistics, with specific examples (annual trends, type breakdown, top institutions, open-access percentage, topic distribution). It effectively distinguishes from sibling tools like openalex_search_works, which is for searching individual works.

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 provides explicit use cases and mentions combining with 'filters' referencing openalex_search_works syntax. It implies when to use aggregate vs search but does not explicitly state when not to use it or alternative tools for other tasks.

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