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

The description discloses the cost per call ($0.01/call), which is important for agents to consider. It does not explicitly mention side effects or read-only status, but the nature of a feed tool implies no side effects beyond the API call itself.

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 relatively concise and includes a compact example. The inclusion of the cost and example in the same paragraph makes it slightly less scannable, but overall it is efficient and not overly verbose.

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 minimal schema, the description provides sufficient context about the tool's functionality and parameters. Since there is no output schema, it does not need to describe return values, and the description covers the required usage context adequately.

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 only defines a generic 'params' object with additionalProperties allowed, so it provides no field-level semantics. The description compensates by specifying the actual fields (mode, q, maxItems) and their allowed values, including an example, giving full parameter meaning.

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: it provides a Hacker News feed with top, new, and best stories plus full-text search. It also lists the data fields (titles, scores, comment counts, author), making the resource and operation unambiguous.

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 includes example parameters and explains the mode options, which gives some usage guidance. However, it does not explicitly state when to use this tool over similar sibling tools (e.g., serp, paper_search), leaving the selection to the agent's inference.

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