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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description doesn't need to restate safety. It adds valuable behavioral context by explaining the return format (structured list with context snippets), market coverage, and the market parameter behavior (omit or [] for all, order no priority). It doesn't mention pagination or error conditions, but that's acceptable given the read-only nature and no output schema.

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 well-structured and front-loaded with the primary use and alternative. Each sentence serves a purpose: differentiating from run_sql, describing the knowledge base, coverage, parameter behavior, example, and a final constraint. It avoids fluff and is easy to scan.

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 moderate complexity (2 parameters, no output schema), the description covers all essential aspects: purpose, usage, parameter details, return type, and alternatives. It explains the return format sufficiently for an agent to understand what to expect, and the market filtering is thoroughly documented.

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%, providing baseline of 3. The description adds extra meaning by giving a natural-language example, specifying lowercase market values, and clarifying that list order doesn't set priority—details that go beyond the schema's own description. This enhances the agent's understanding of how to construct valid inputs.

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 is for qualitative company discovery, naming the resource (company knowledge base) and its scope (industry, business model, supply chain, competitors, management). It explicitly differentiates from sibling tool run_sql for numerical screening, making the purpose unambiguous.

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?

Provides explicit when-to-use (qualitative discovery) and when-not-to-use (numerical screening → use run_sql on company_snapshot). Also states the tool is ONLY for finding a list of companies by description, clearly separating it from other sibling tools.

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