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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds meaningful beyond-annotation behavior: ranked results with a matching snippet, a hard-exclude rule for must_include, the 50-per-call bound, and the total_count field. This gives the agent a clear picture of pagination and result semantics without contradicting the annotations.

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 about 70 words, front-loaded with the core purpose, and each sentence delivers distinct value: what it searches, when to use it, the must_include behavior, result format, exact-lookup alternative, and pagination cap. There is no filler or redundancy.

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 complexity of the filters and the existence of an output schema, the description covers most operational needs: search scope, filter combination, must_include semantics, result ranking and snippet, the 50-row bound, and the pagination indicator. The only notable missing piece is the mode parameter semantics, but the enum values are somewhat self-explanatory and the output schema fills return-value details.

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 50%, so the description needs to compensate. It does add value for must_include ('hard-exclude candidates whose corpus lacks them') and gives example filter fields (status, location, owner, custom fields). However, it never explains the mode parameter (hybrid/semantic/exact), which is required and undocumented in the schema, leaving an important semantic gap.

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 opens with a specific verb and resource: 'Finds candidates by meaning across profile, CV text, recruiter notes, and call or meeting summaries.' This clearly distinguishes the tool from exact-lookup siblings by emphasizing semantic/full-text search over candidate-related texts. It also names the sibling it is not ('Use list_records instead for exact structured lookups'), so an agent can immediately tell which tool fits.

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 states when to use the tool ('Use for skills, experience, background, or things a candidate said') and how to constrain it with filters. It provides a direct alternative with the condition for choosing it ('Use list_records instead for exact structured lookups'), giving the agent actionable routing guidance.

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