search_lookups

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 says the tool finds reference/lookup tables and suggests downstream tools, but it does not disclose what the search returns, how results are ordered, whether matches are approximate or exact, or any pagination/limit behavior. This leaves important execution behavior unexplained.

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 short and front-loaded with the core purpose, which is good. However, the '→ get_reference → lookup' notation is cryptic and interrupts the natural reading flow. It earns some value by suggesting follow-ups, but it is not presented in a clear, structured way.

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, no annotations, and 0% parameter documentation, the description alone must give an agent enough context to invoke the tool correctly. It provides examples and a follow-up chain, but it omits the return shape, result semantics, and how the query/top_k parameters affect behavior, leaving the tool incompletely specified.

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%, and the description does not explain the 'query' or 'top_k' parameters directly. The examples ('sensor sizes, f-stops, pixel formats') weakly suggest what queries may contain, but the description does not clarify how top_k affects results or what format the query should take, so it does not sufficiently compensate for the missing schema documentation.

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 names a specific action ('Find') and a clear resource ('reference/lookup tables'), with concrete examples such as sensor sizes, f-stops, and pixel formats. This distinguishes it from general search tools and gives an agent a clear idea of the tool's domain, though the arrow notation adds mild ambiguity.

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 when to use this tool: when searching for reference/lookup tables rather than documents, calculators, or products. The 'get_reference → lookup' chain hints at the expected follow-up workflow, but there is no explicit statement of when not to use this tool or how it compares to alternatives like search_knowledge_base.

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