check_readability

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

No annotations are provided, and the description only mentions return values. It lacks behavioral details such as input requirements (e.g., text length, language support) or side effects, leaving an agent uninformed about how the tool operates.

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 a single concise sentence that efficiently communicates the tool's purpose and output without any redundant or extraneous 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 single parameter and missing output schema, the description provides a reasonable overview of return values. However, for a tool returning structured data, the format is unspecified, which may hinder an agent's ability to parse 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?

The sole parameter 'content' is already well described in the schema as 'The content to analyze' (100% coverage). The description adds no further semantic value beyond the schema, so a baseline score of 3 is appropriate.

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 analyzes readability and lists specific metrics returned (Flesch-Kincaid score, grade level, sentence stats, reading time). This distinguishes it from sibling tools like analyze_keyword or score_content, which focus on other aspects.

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 for readability analysis but does not provide explicit guidance on when to use this tool over alternatives or mention any prerequisites or limitations.

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