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 output format (a nested dictionary with URLs) but does not mention any behavioral traits such as rate limits, authentication requirements, error conditions, or whether it's a read-only operation. For a tool with zero annotation coverage, this is a significant gap in transparency.

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 concise with two sentences, but it mixes Japanese and English, which may reduce clarity for some agents. The structure is front-loaded with the main purpose, but the second sentence redundantly restates the return value in a less clear format. Some sentences could be more efficient in conveying 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?

Given the tool's complexity (simple read operation with no parameters) and lack of annotations and output schema, the description is partially complete. It explains the output format but lacks details on behavioral aspects like error handling or performance. For a zero-parameter tool, this is adequate but leaves gaps in operational context.

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 0 parameters, with 100% schema description coverage (since there are no parameters to describe). The description does not need to add parameter semantics, and it appropriately focuses on the output. A baseline score of 4 is applied for zero-parameter tools, as there is no parameter information to compensate for.

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: to return a dictionary of the Sakura Cloud manual's table of contents with item names and corresponding URLs. It specifies the verb ('返します'/'returns') and resource ('さくらのクラウドの使い方のマニュアルの目次'). However, it does not explicitly differentiate from sibling tools like 'get_api_manual_outline' or 'read_manual', which appear related to manual access, so it misses full sibling differentiation.

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 does not mention sibling tools such as 'get_api_manual_outline' or 'read_manual', nor does it specify any context or prerequisites for usage. This lack of guidance leaves the agent to infer usage from tool names alone.

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