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

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context beyond annotations: returns up to 50 profile-first results, emails are hidden, costs 0 credits, and one call covers multiple criteria. This gives the agent a clear picture of side effects and limitations, though it doesn't cover every possible behavior.

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 three sentences with no fluff. It front-loads the core purpose, then adds critical usage constraints, alternatives, and examples in a compact, scannable format. Every sentence earns its place.

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, no output schema), the description covers the essential context: what it finds, how many results, email visibility, cost, and when not to call it. It lacks a detailed description of the return structure, but 'profile-first results' gives a reasonable expectation. It adequately handles the most important operational concerns.

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 only 40%, so the description needed to compensate. It adds general meaning via examples like 'funded SaaS companies' and 'AWS customers', implying use of industry, funding_status, and technologies filters. However, it does not explain most optional parameters (limit, location, company_size, hiring_growth, revenue_growth) and relies on the schema for Mode A/B distinctions. It provides partial but not complete compensation for low schema coverage.

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 a specific verb and resource: 'Find people with a specific title/role at companies matching given criteria.' It distinguishes itself from sibling tools like find_email by noting emails are hidden and from generic search tools by focusing on people at companies. Concrete examples ('CTOs at funded SaaS companies') further clarify intent.

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 explicitly provides usage guidance: 'do NOT call it repeatedly per company; one call covers the criteria' and names the alternative tool for revealing emails ('Reveal an individual email with find_email'). This is exactly the kind of when/when-not guidance needed, and it also clarifies credit costs.

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