surf

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

The annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds meaningful behavioral context beyond that by stating the tool does not host, publicly list, or register the API, and that results are returned only to the caller. This clarifies privacy and side-effect expectations.

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 compact and front-loaded. The primary action and input are in the first clause, and the privacy/side-effect statement is separated clearly. Every sentence contributes useful information without repetition.

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?

The description covers what the tool returns, how to use it, and its side-effect-free behavior, which is sufficient given the annotations. It does not describe potential failures or the quarantine behavior in the description itself, but the input schema already documents quarantine for from_docs results.

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?

Input schema coverage is 100%, so both parameters are already documented. The description reinforces the meaning of from_docs and url by mentioning human docs pages and OpenAPI URLs, but it does not add significant new semantic detail 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 the tool's purpose: submit an API URL and receive agent-ready tools and artifacts. It names the resource (API spec or docs page) and the action (comprehend), but it does not explicitly contrast itself with the sibling list_surfaces.

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 explains when to use from_docs for human docs pages instead of OpenAPI URLs, which provides some usage context. However, it never mentions the sibling tool list_surfaces or gives explicit guidance about when to prefer one tool over the other.

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

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

Annotations already establish that the tool is read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond those annotations, including that it is free, instant, and limited to what the public index lists. No contradiction exists.

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 three short, purposeful sentences. It front-loads the core listing behavior, immediately provides the target use case, and ends with useful constraints. No filler or redundant repetition of schema information.

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 simple zero-parameter list tool with strong annotations, the description fully covers what the tool returns, when to use it, and important limitations. The absence of an output schema is compensated by describing the result type: API surfaces with MCP URLs.

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 tool has zero parameters and the schema is empty with full coverage, so there is no parameter information the description needs to add. This matches the baseline for a parameterless tool.

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 function: list every API surface on this host along with the MCP URL for reconnecting. The phrasing distinguishes it as a discovery/index tool rather than a comprehension tool like the sibling comprehend_api.

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 gives an explicit use case: 'Use it when you landed on the host root and need a specific API.' This provides clear context, though it does not explicitly mention when to prefer comprehend_api or state exclusions.

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