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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, indicating safe, non-destructive read operations. The description adds valuable behavioral details: it returns the top-N most relevant tools with names, descriptions, and full input schemas, and states each result is 'ready to call directly, no second schema lookup needed.' This goes beyond annotations and helps the agent understand the tool's outputs and usage pattern.

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 two sentences, both front-loaded and substantive. The first sentence states the core purpose, and the second explains when to use it and what it returns. There is no extraneous information, and each sentence earns its place. It is concise yet complete.

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 that there is no output schema, the description adequately explains the return format: a list of tools with names, descriptions, and full input schemas. It covers the key aspects: purpose, usage timing, and output quality. It could potentially mention pagination or result limits, but the limit parameter addresses that indirectly. Overall, it is complete enough for an agent to decide when and how to use this tool.

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 100%, with parameters for query (and aliases) and limit. The description provides examples ('look up FDA drug approvals', 'analyze housing market trends') and explains that the query accepts natural language. While the schema already covers the parameter details, the description adds context by illustrating typical input patterns, which is mildly helpful but does not significantly extend the schema's meaning.

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's purpose: 'Find tools by describing the data or task.' It also lists specific domains (SEC filings, financials, FDA drugs, etc.), making the scope concrete. The verb 'find tools' distinguishes it from sibling tools that perform specific analyses (e.g., compare_entities, deep_research), so the agent can differentiate.

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 advises: 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' This provides clear when-to-use guidance. It does not list explicit when-not or alternatives, but the sibling list and the recommendation to use first imply it is for exploration before selecting other tools.

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