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

Annotations already declare read-only and idempotent behavior. The description adds value by disclosing the return format ('top-N most relevant tools with names, descriptions, and full input schemas') and noting that results are ready to call directly with no second schema lookup, which is useful behavioral context beyond 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 front-loaded with the core purpose, uses a compact list of covered data domains, and each sentence contributes to understanding the tool's behavior and use. The domain list is lengthy but informative, and the overall structure is clear and efficient.

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 simplicity and fully described schema, the description covers when to use it, what it returns, and the depth of results. With no output schema, the explicit description of return format (top-N with full schemas) gives the agent sufficient expectations for invocation and follow-through.

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% description coverage, including aliases and limits. The description does not add significant parameter-level semantics beyond what the schema already provides; it repeats the 'describing the data or task' idea but offers no new detail. Baseline 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 states a specific verb+resource ('Find tools') and enumerates the domains it covers (SEC filings, FDA drugs, FRED, etc.), which clearly distinguishes it from sibling tools like search_datasets or validate_claim. The purpose is unambiguous and identity is well-defined.

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?

It provides explicit usage context ('Use when you need to browse, search, look up, or discover what tools exist') and tells the agent to 'Call this FIRST' when many tools are available, which strongly signals precedence over other search tools. It doesn't explicitly name alternatives, but the 'first' guidance effectively directs selection.

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