workspace_search_theorems

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 the scope ('active workspace') but does not clarify search semantics such as exact vs. fuzzy matching, case sensitivity, whether filtering by kind or paper_id narrows scope, or whether the operation is read-only. The description is too thin for a search tool with no annotation support.

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, front-loaded sentence with no filler. Every word contributes to the core purpose, making it easy for an agent to parse quickly.

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 four parameters, no annotations, and several closely related sibling tools, the description is under-specified. It does not explain how filters interact, what counts as a match, or when this tool should be chosen over list_theorems or get_theorem. The presence of an output schema reduces the need to describe return values, but significant operational context is still missing.

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 0%, so the description must compensate, but it only explains the general search target ('theorem titles and bodies'). It does not clarify the meaning of 'kind', 'paper_id', or 'limit'. The query parameter's role is inferable from the description, but the filter and pagination parameters are left entirely to the schema.

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 specifies a clear verb ('Search'), a resource ('theorem titles and bodies'), and a scope ('across the active workspace'). This distinguishes it from sibling tools like list_theorems and get_theorem, which imply enumeration and single-item retrieval respectively.

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 query-based search across the active workspace, but it does not explicitly state when to prefer it over list_theorems, get_theorem, or where_used. No alternative tools or exclusions are mentioned, leaving usage conditions somewhat inferred.

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