sacloud-mcp

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the conversion to markdown and content extraction but lacks critical details: error handling (e.g., invalid URLs), rate limits, authentication needs, output format specifics beyond 'str', or whether it's a read-only operation. For a tool with no annotations, this leaves significant behavioral gaps.

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 appropriately sized and front-loaded: the first sentence clearly states the purpose, followed by structured 'Args' and 'Returns' sections. There's minimal redundancy, though the 'Returns' section slightly repeats information from the first sentence. Overall, it's efficient and well-organized.

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 tool's moderate complexity (involving URL processing and markdown conversion), no annotations, and no output schema, the description is partially complete. It covers the basic purpose and parameters but lacks details on behavioral traits, error handling, and output specifics. It's adequate as a minimum viable description but has clear gaps for effective agent use.

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 description includes an 'Args' section that documents the single parameter 'url' as a string for the Sakura Cloud API manual URL. With 0% schema description coverage, this adds essential meaning beyond the bare schema. However, it doesn't provide examples, format constraints (e.g., URL validation), or details on what constitutes a valid manual URL, leaving some ambiguity.

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 takes a Sakura Cloud API manual URL, converts it to markdown, and extracts main content. It specifies the verb ('受け取り、markdownに変換し、取得します'), resource ('さくらのクラウドのAPIマニュアル'), and transformation process. However, it doesn't explicitly differentiate from sibling tools like 'read_manual' or 'read_object_storage_api_manual' beyond the URL specificity.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_api_manual_outline' or 'read_manual', nor does it specify prerequisites, constraints, or typical use cases. The only implicit context is the URL requirement, but no explicit usage guidelines are given.

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