coleman_liau_index

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

No annotations provided, so description fully responsible. It indicates a computation (character and sentence counts) but does not disclose any limitations, edge cases, or behavioral traits beyond the formula. Minimal transparency for a simple function.

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?

Description is very short (one sentence) and to the point. It front-loads the tool's name and purpose. While concise, it could benefit from slightly more structure, but it is not verbose.

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 simple nature of the tool and presence of an output schema, the description is minimally complete for understanding the return value. However, missing usage guidance and parameter details reduce completeness for an agent seeking to select among sibling 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?

Input schema has 0% description coverage for the single 'text' parameter. Description only mentions characters per word and sentences per word, but does not explain parameter constraints, expected format, or encoding. Fails to compensate for lack of schema documentation.

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?

Description clearly states the tool computes a grade level using the Coleman-Liau formula based on characters per word and sentences per word. It distinguishes itself from sibling readability indices by naming the specific index and its formula components.

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 like automated_readability_index or flesch_kincaid_grade. The description does not provide any context for selection among the many sibling tools.

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