Japanese Article Quick Check

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

The description discloses that the tool is rule-based, free, and does not use an external AI API, which is useful behavioral context. However, it does not explain what the output looks like, whether the tool modifies anything, or any limitations of the rule-based approach. Since no annotations are provided, the description carries the full burden, and while it adds some transparency, it leaves the return format and side-effect profile undisclosed.

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 and front-loaded with the core purpose ('Free rule-based checker for Japanese articles'), followed by a list of checks and a clarifying note about no external AI API. Every sentence earns its place, though the list of checks is somewhat dense and could be structured more clearly.

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 single-parameter tool with no output schema and no annotations, the description covers the input and the tool's scope well. However, it does not describe the output format, how results are returned, or any limitations of the rule-based approach. An agent would know what the tool does but not what to expect from the response, which is a notable gap for a tool with no output schema.

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 description coverage is 100%: the only parameter, 'text', is described as the Japanese article body to audit. The description adds context about what the tool checks, but it does not add syntax, formatting, or additional parameter semantics beyond the schema. Baseline 3 is appropriate because the schema already documents the parameter fully.

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: a free rule-based checker for Japanese articles. It lists specific checks (strong claims, duplicate text, PR disclosure, commercial links, URLs, long sentences, basic article quality) and explicitly notes no external AI API is used, which distinguishes it from AI-based alternatives.

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 implies usage: it is for checking Japanese articles, and the input schema requires the article text. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. With no sibling tools listed, the lack of alternative routing is less critical, but the description could still clarify the intended use case more directly.

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