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

Beyond the annotations (readOnly, openWorld), the description adds genuinely useful context: the cost model ($0.002 USDC per successful call, failed calls free), the payment rails (x402 on Base/Solana/Arc), the API version, the CC BY-SA attribution obligation, and the 600-character answer truncation. These are non-obvious behavioral traits that materially affect how an agent calls 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 purpose and return fields are front-loaded, followed by the answer-truncation detail, licensing, API version, and pricing. Every sentence earns its place, though the pricing sentence is dense and could be split.

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?

With readOnly/openWorld annotations and an output schema, the description only needs to cover operational details — and it does: cost, payment, attribution, and answer truncation are all stated. Minor gaps like whether limits apply to returned answers or questions are not material.

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 coverage is 100%, so baseline is 3, but the description adds value by explaining that answers=1 pulls only the first 600 characters of the accepted answer and that accepted filters to questions with an accepted answer — details absent from the terse schema strings. This is above the schema baseline.

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 first sentence names a specific verb (search questions) and resource (Stack Overflow), and enumerates the returned fields (title, score, answer count, accepted flag, tags, link). An agent can tell this apart from sibling search tools like hn_search or github_search without opening a schema.

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 frames the query modes (words, optional tags, accepted status) and what the answers=1 flag enables, which implies usage. However, it never states when to prefer this over alternatives such as pubmed, arxiv, or hn_search, and offers no exclusions or prerequisites.

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