clarity_score

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

The description indicates a read-only calculation but provides no details beyond 'based on readability metrics'. Since no annotations exist, the description carries full burden but lacks specifics like output format or computational complexity.

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 extremely concise, with a single sentence for purpose and one parameter line. It is front-loaded and wastes no words, but could be structured with clearer separation of purpose and parameters.

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 presence of an output schema (inferred), the description is minimally sufficient for a simple calculation tool. However, it lacks examples, use cases, and differentiation from many sibling readability tools.

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 a brief explanation of the single parameter 'text'. With 0% schema description coverage, this minimal addition compensates partially but could be more informative about expected input length or encoding.

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 action (Calculate) and resource (clarity score for text) and mentions it is based on readability metrics. However, it does not differentiate among sibling tools like analyze_readability or specific readability formulas.

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?

No guidance on when to use this tool versus alternatives such as analyze_readability, dale_chall_score, or fry_readability. No context about prerequisites or when not to use.

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