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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds valuable context: the pagination limit (only first 100 results), the JSON output with a results array, and the dual text/structured views. It doesn't contradict the annotations and provides useful operational detail.

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 longer than typical but well-structured: it opens with the core purpose, then systematically explains free-text, structured filters, pagination, output format, and the relationship to get_person. Every section earns its place; the MCP Apps note is relevant for apps that support cards. It is front-loaded and logically ordered, though it could be tightened slightly without losing meaning.

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 complexity (10 parameters, enums, pagination, output format), the description is remarkably complete. It covers the pagination limit, the JSON output structure, the exclusion of contact info, and the dual views. It does not need to explain return values because an output schema exists. Nothing critical is missing for an agent to call it correctly.

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 each parameter already has a detailed description, including the OR/AND semantics for category, skills, and lookingFor, and the enum meanings for workType. The tool description largely repeats this information without adding substantial new meaning beyond the schema. It does clarify the requirement to provide at least one filter/query, but that's a usage rule, not parameter semantics. Baseline 3 is appropriate.

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 states a specific verb ('search'), a clear resource ('public Foundaree profiles'), and distinguishes itself from the sibling get_person by explicitly noting that results never include phone/emails and that get_person is for contact details. The scope is precise: free-text and/or structured filters, with a requirement to provide at least one.

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 explicitly says when to use get_person instead ('use get_person for one profile's public contact details') and advises adding filters to narrow the search when the result set is large. It doesn't mention match_people, but that's a separate matching tool likely for a different purpose; the core guidance is clear and actionable.

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