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

Annotations already declare the tool is read-only, idempotent, and non-destructive. The description adds valuable behavioral context beyond this: it returns top-N tools with names, descriptions, and full schemas, and 'each result is ready to call directly, no second schema lookup needed.' It also states it should be called first, which is a behavioral trait. This adds context without contradicting 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 three sentences: purpose, usage contexts, and return behavior/usage advice. Each sentence earns its place, is front-loaded with the main verb, and avoids fluff. The list of domains is compact but informative. There is no redundancy with the schema or annotations.

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?

Despite having no output schema, the description explains what the return value contains: 'top-N most relevant tools with names, descriptions, and full input schemas (with curated examples).' It also specifies the parameter limit behavior via schema. Given the tool's simplicity and the richness of the description, it fully covers the user's need to understand when and how to use it.

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 all parameters have descriptions (query, aliases, limit). The description does not add much beyond the schema, though it reinforces the natural-language nature of the query with examples like 'look up FDA drug approvals' in the schema's examples. Since the schema carries the semantic weight, a baseline score of 3 is appropriate.

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 specifies the verb (find), the resource (tools), and the input (description of data/task). It also distinguishes itself from sibling tools by framing itself as a meta-tool for discovering other tools, especially with the phrase 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).'

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 provides explicit when-to-use guidance: 'Use when you need to browse, search, look up, or discover what tools exist for: [list of domains].' It also gives a clear directive: 'Call this FIRST when you have many tools available.' This implies when not to use it (when you need one answer) and lists specific use cases, effectively distinguishing it from alternatives.

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