blackmount-nlp-mcp

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

No annotations are provided, so the description carries full burden. It mentions the index is 'based on characters per word and sentences per word,' which gives some behavioral insight into the calculation method. However, it lacks critical details like output format (though an output schema exists), error handling, or performance characteristics (e.g., speed, limitations). For a tool with no annotations, this is a significant gap.

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—two brief sentences that directly state the tool's function and basis. Every word earns its place with zero redundancy, making it easy to parse quickly while conveying essential 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 moderate complexity (a readability index calculation), no annotations, and an existing output schema, the description is minimally complete. It explains what the tool does but lacks usage context, behavioral details, and parameter guidance. The output schema mitigates some gaps, but overall completeness is limited.

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 0%, with one parameter 'text' undocumented in the schema. The description doesn't add any parameter-specific information beyond the tool's purpose. However, with only one parameter and a clear tool name, the baseline is adequate but not compensatory for the 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?

The description clearly states the tool calculates 'Coleman-Liau Index' and explains it provides 'Grade level based on characters per word and sentences per word.' This specifies the verb (calculate index) and resource (text analysis), though it doesn't explicitly differentiate from sibling readability tools like 'flesch_kincaid_grade' or 'automated_readability_index' that serve similar purposes.

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. With multiple readability/grade-level siblings (e.g., 'flesch_kincaid_grade', 'gunning_fog_index', 'smog_grade_index'), there's no indication of which contexts or text types this index is best suited for, nor any prerequisites or exclusions mentioned.

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