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 'Porter stemmer from scratch' which implies a specific algorithmic implementation, but doesn't disclose behavioral traits like error handling (e.g., for non-English words), performance characteristics, or what the output looks like (though output schema exists). The example helps but is minimal.

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 appropriately sized and front-loaded: two concise sentences that directly state the tool's function and provide an illustrative example. Every sentence earns its place with no wasted words or redundant 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 (stemming algorithm), no annotations, and an output schema (which handles return values), the description is minimally complete. It covers the core purpose and parameter semantics but lacks usage guidelines and detailed behavioral context, making it adequate but with clear gaps for effective agent use.

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%, but the description compensates by explaining the 'word' parameter's purpose through the example ('running' -> 'run'). It adds meaning beyond the bare schema by showing what the input represents and what transformation occurs. With only one parameter, this is sufficient for clarity.

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 purpose: 'Reduce word to its stem' with a specific example ('running' -> 'run'). It distinguishes from siblings by focusing on stemming rather than cleaning, counting, or analyzing text. However, it doesn't explicitly differentiate from potential similar tools (though none are present in siblings).

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 is provided. The description mentions 'Porter stemmer from scratch' which implies a specific algorithm, but doesn't explain when stemming is appropriate compared to other text processing tools in the sibling list (like cleaning or tokenization).

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