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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false. The description adds valuable behavioral context: it returns 'top-N most relevant tools with names, descriptions, and full input schemas (with curated examples)' and notes that results are 'ready to call directly, no second schema lookup needed.' This exceeds what annotations provide.

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, front-loaded with the primary purpose ('Find tools by describing the data or task.'). Each sentence is efficient and informative, covering usage context, output features, and a call-to-action ('Call this FIRST...'). No redundant or filler content.

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 complexity (discovery tool with multiple aliases, broad domain coverage), the description, schema with examples, and annotations together provide complete context. The description explains the output format ('names, descriptions, and full input schemas') without needing an output schema. It is fully sufficient for an AI to decide when and how to invoke 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?

The input schema has 100% parameter description coverage, so the baseline is 3. The description adds meaning by listing example domains (SEC filings, financials, FDA drugs, etc.) that clarify appropriate query topics. It also notes that 'query' accepts multiple aliases, which helps the agent understand flexibility. The examples in the schema further supplement this.

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 uses specific verbs ('discover') and identifies the resource ('tools'). It distinguishes from sibling tools by emphasizing this is for browsing/exploration before direct tool calls.

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: '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.' It provides clear context but does not explicitly exclude other scenarios, such as when the exact tool is already known.

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