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

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond annotations: it explains that results include 'names, descriptions, and full input schemas (with curated examples)' and that 'each result is ready to call directly, no second schema lookup needed.' This clarifies the non-destructive, convenient nature of the tool.

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 long, front-loaded with the primary purpose. The middle sentence contains a long list of domains, which, while informative, slightly reduces conciseness. Overall, every sentence adds value, but the list could be more succinct.

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?

There is no output schema, so the description compensates well by stating the output format: 'top-N most relevant tools with names, descriptions, and full input schemas.' It also mentions default limit (20) and max. The tool is a discovery meta-tool, and the description covers its behavior adequately. A minor gap: it does not explicitly state that it searches only among available tools (not external data), but that is implied.

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 the schema already documents each parameter thoroughly. The description enhances by providing natural language usage context and examples (e.g., 'analyze housing market trends', 'look up FDA drug approvals'), which helps an agent understand semantic intent beyond parameter names.

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 'Find tools by describing the data or task,' clearly stating the tool's purpose as a discovery mechanism. It lists numerous specific domains (SEC filings, financials, FDA drugs, etc.) and contrasts with sibling tools like ask_pipeworx or entity_profile, which are specialized data retrieval tools.

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 directs to 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' It also specifies when to use: 'browse, search, look up, or discover what tools exist for...' This provides strong context for both when and when not to invoke the tool.

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