lookup_users

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

With no annotations provided, the description carries full burden and adds significant behavioral context beyond the input schema. It discloses pagination behavior ('fetch all pages and return every user in one response'), caps ('cap 500'), and interaction patterns ('if multiple, ask which one'). It also explains how parameters interact ('Ignored when return_all=True').

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 appropriately sized but not optimally structured. It starts with a clear purpose statement, but then mixes parameter explanations with usage guidance in bullet points. Some redundancy exists (query explanation appears twice). While all content is valuable, the organization could be more front-loaded and streamlined.

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?

Given 4 parameters with 0% schema coverage and no annotations, the description provides comprehensive parameter semantics and behavioral context. The existence of an output schema means return values don't need explanation. The description covers search patterns, pagination, caps, and downstream usage, making it largely complete for this lookup tool.

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?

With 0% schema description coverage, the description fully compensates by explaining all 4 parameters in detail. It provides syntax examples ('firstName:last', 'name:Last'), default behaviors ('leave default to list all'), constraints ('max 50', 'cap 500'), and parameter interactions ('Ignored when return_all=True'). This adds substantial meaning beyond the bare 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 clearly states the tool's purpose: 'Look up users by name, or list all users in the system.' It specifies the verb ('look up') and resource ('users'), and distinguishes between search and list operations. However, it doesn't explicitly differentiate from sibling tools like 'search_leads' beyond implied scope differences.

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 clear context for when to use specific features: 'Use return_all=True... to fetch all users' and 'For name search: query in field:value form... If one user is found, use that ID in search_leads; if multiple, ask which one.' It gives practical guidance on parameter combinations and downstream actions, though it doesn't explicitly state when NOT to use this tool versus alternatives.

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