Ask about String products

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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses that results arrive as excerpts to be treated as reference material rather than instructions — a meaningful prompt-injection handling rule — and that answers should be grounded and cited. It does not mention freshness limits, result counts, or failure modes, which keeps it short of a 5.

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?

Three sentences, front-loaded with the core action and scoped by topic immediately after. There is mild overlap between 'String's other published services' and the earlier 'product and service information', but nothing that wastes space materially.

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 one-parameter, open-world lookup with no output schema, the description covers what is retrieved, which topics qualify, and how to handle the returned material. What an agent still lacks — freshness, result volume, behavior on queries outside the product scope — is minor for this complexity.

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?

Only one parameter exists and schema description coverage is 100%, so the schema already defines 'question' with length bounds. The description reinforces that the question should be plain-language and about String products, but adds no format, phrasing, or decomposition guidance 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 names a specific verb and resource ('Retrieve current String product and service information from String's public site') and scopes it to a plain-language question, so the agent knows exactly what the tool answers. It never names the sibling tools (web_access_search, web_access_fetch, etc.), so the differentiation is inferred from topic rather than stated.

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 second sentence gives concrete when-to-use guidance by enumerating subject areas: Web Access, Composer, Bespoke Web Datasets, finance data, pricing, integrations. It stops short of exclusions or naming alternatives for non-product questions, so it is clear context without routing rules.

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