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

Annotations already mark it as read-only, idempotent, and non-destructive. The description adds valuable behavioral context: it returns top-N tools with full schemas and examples, and each result is 'ready to call directly, no second schema lookup needed.' This explains the return behavior beyond what annotations cover.

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 a bit longer than minimal but every sentence carries weight: main purpose, use case list, return value, and strategic advice. The domain list is useful for prompting but could arguably be shorter. It is front-loaded with the core function, so structure is effective.

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?

For a discovery tool with no output schema, the description fully covers what it does, when to use it, what it returns (top-N with full schemas), and how to invoke it efficiently. It even notes that no second schema lookup is needed, addressing a common user concern. The coverage is complete.

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 each parameter including aliases and a natural language description. The tool description adds value by providing a broad list of example domains (e.g., FDA drugs, FRED economic data, ATTOM real estate) and stating that queries can be task descriptions like 'analyze housing market trends,' which enriches the user's understanding of query formulation beyond the schema.

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 'Find tools by describing the data or task' with a specific verb and resource, and it lists concrete domains (SEC filings, financials, FDA drugs, etc.). It distinguishes itself from siblings by being a meta-tool for discovering other tools, especially given the sibling names like search, search_within, and item.

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 guidance: '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 clearly indicates when to use it over directly invoking a known tool.

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