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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral context beyond annotations: that it returns 'top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed.' This explains the output format and efficiency, which is not covered by 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 somewhat lengthy but well-structured: it starts with the core purpose, lists examples, then explains the return format. Every sentence adds value. However, the list of data domains could be slightly shortened without losing clarity. Overall, it earns its length.

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 (discovery across many domains) and the absence of an output schema, the description adequately explains what the tool returns (tool names, descriptions, full schemas with examples). Parameter documentation is complete, and usage guidance is provided. No gaps are evident.

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%, so baseline is 3. The description adds extra value by providing examples of valid queries ('look up FDA drug approvals', 'analyze housing market trends') and explaining that the 'limit' parameter controls the top-N results. This enhances understanding beyond the schema's property descriptions.

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 lists many specific use cases (SEC filings, FDA drugs, etc.), which distinguishes it from sibling tools that are domain-specific. The verb 'discover' combined with 'top-N most relevant tools' makes the action 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?

The description explicitly says 'Use when you need to browse, search, look up, or discover what tools exist for...' and 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' This provides clear guidance on when to use the tool, implying alternatives (other specific tools) when the user already knows what they need.

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