Person

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

Annotations already declare readOnly, idempotent, closed-world, non-destructive, so safety is covered; the description adds behavior annotations cannot express: fuzzy name/email matching and a graceful no-match fallback that returns candidate names. That fallback behavior is exactly the kind of detail an agent needs to interpret an empty or unexpected result.

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?

Two sentences, front-loaded with the payload, then the matching contract. Nothing redundant and nothing padded.

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?

An output schema exists, so return structure need not be explained, and the description covers contents, matching, and the no-match path. The one gap is the ambiguous case of multiple people matching the same name, which is not addressed for a name-keyed lookup.

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 coverage is 100% and the schema already documents the single 'name' parameter as a name or email. The description still adds value by stating the match is spelling-tolerant ("in any spelling"), which tells the agent it can pass informal or partial forms.

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 verb (get) and resource (one colleague) and enumerates exactly what is returned: notes, email addresses, open promises, and the last meeting. "One colleague" implicitly separates it from the bulk sibling list_people, but no sibling is named explicitly, so differentiation requires a small inference.

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?

It tells the agent when this tool applies (looking up a single person by name or email, in any spelling) and what happens on a miss (returns known names). It stops short of explicit exclusions or pointing to alternatives such as list_people for browsing, but the usage context is clear.

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