search_people

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

No annotations are provided, so the description carries the full burden. It discloses the return format (list with name, job_title, profile_url) and the empty-list behavior for no matches. Though it doesn't explicitly state auth requirements or side effects, the verb 'search' implies a read-only operation, and the return details are helpful. A score of 4 reflects this good but not exhaustive disclosure.

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 well-organized docstring with separate Args and Returns sections. It is concise, front-loaded with the primary purpose, and every sentence adds value—no filler or repetition. The structure makes it easy 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?

Given the tool's simplicity (one parameter, no nested objects), the description is fully complete. It covers the input semantics, output structure, and edge-case behavior. The presence of an output schema for return values is indirectly supported by the explicit return description, so nothing important is 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?

The schema has 0% description coverage for the single 'query' parameter, but the description fully compensates by explaining that it should be a name or partial name. This adds meaning beyond the raw string type in the schema, so the description carries the semantic weight effectively.

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: 'Search the 1Password/AgileBits employee directory (ChartHop) by name.' It uses a specific verb ('search'), identifies the resource ('employee directory'), and specifies the filter ('by name'). This distinguishes it from any potential sibling tools, though none are listed.

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 on how to use the tool: pass a name or partial name as the query. It does not explicitly mention alternative tools or when-not-to-use, but no siblings exist. The guidance 'A name (or partial name) to look up' is direct and sufficient for most use cases.

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