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

With no annotations, the description takes on the full transparency burden. It discloses the search order (server first, then catalog), the return payload (method, URL, price, how to call), and a critical cost detail ('Free'). This goes beyond basic operation and gives the agent a clear behavioral model, though it could mention result limits or failure 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 two sentences long, front-loaded with the core instruction, and wastes nothing. The second sentence efficiently adds the search scope and the free pricing note. Every phrase earns its place.

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?

For a tool with a single parameter and no output schema, the description is remarkably complete. It covers what the tool does, what input to provide, how the search is performed, and what the output will contain (method, URL, price, how to call them). The absence of an output schema is compensated by this explicit listing.

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 schema already documents 'task' with a description and example, and with 100% schema coverage, the baseline is 3. The description adds value by providing multiple diverse examples ('Apple risk factors 2023', 'is this token a honeypot', etc.) and reinforcing that plain-language input is acceptable, enriching the meaning beyond the schema.

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 its function: searching server datasets and the Professor Sausages catalog to return matching endpoints. It uses a specific verb ('searches') and specifies the resource (server datasets, catalog), and it distinguishes itself from sibling tools as a meta-discovery tool rather than a specific data endpoint.

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 gives clear context: it describes what the user should do ('Describe the data you need in plain language') and provides concrete examples. It implies this is the tool for finding data endpoints, but it does not explicitly state when not to use it or mention alternatives, so it misses the explicit exclusion that would warrant a 5.

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