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

The annotations already declare this as a safe read-only, idempotent operation. The description adds valuable behavioral context: it returns top-N tools with names, descriptions, full input schemas, and curated examples, and explicitly notes that results are ready to call directly with no second schema lookup. This goes beyond the annotations and helps the agent understand the return value, though it doesn't discuss rate limits or error handling.

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 front-loaded with the core purpose, then provides a list of covered domains (which, while long, is useful for matching agent intents), and ends with the output format and a strong usage directive. Every sentence earns its place, and the structure is clear. It is slightly longer than strictly necessary, but the domain list adds significant retrieval value.

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, a rich schema, and strong annotations, the description is mostly complete. It explains the return format (top-N tools with schemas), the use case, and when to call it. The only minor gap is not explaining what 'top-N' means in terms of ranking, but the provided examples and schema cover the essential information an agent needs to invoke it correctly.

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?

The input schema has 100% coverage—every parameter (query and its aliases, limit) has a description. The description itself does not add any parameter-level meaning beyond what the schema already provides, so the baseline score of 3 is appropriate. The examples in the schema (e.g., 'look up FDA drug approvals') are more detailed than anything in the description.

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 opens with a specific verb and resource: 'Find tools by describing the data or task.' It clearly distinguishes itself from sibling tools by being a meta-tool that discovers other tools, rather than performing a specific data task. The scope is further clarified with a list of supported domains (SEC filings, FDA drugs, etc.), leaving no ambiguity about its purpose.

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 states when to use the tool: 'Use when you need to browse, search, look up, or discover what tools exist' and adds a strong trigger: 'Call this FIRST when you have many tools available.' It implies when not to use it ('not just one answer') but does not name specific alternative tools or give explicit exclusions, so it stops short of a perfect 5.

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