blackmount-nlp-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Remove all punctuation') but doesn't specify what constitutes punctuation, whether the removal is destructive to the original text, how it handles edge cases, or any performance considerations. This leaves significant behavioral gaps for a mutation tool.

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, direct sentence with no wasted words, making it highly efficient and front-loaded. Every word contributes to understanding the tool's core function, achieving optimal conciseness.

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 low complexity (one input parameter) and the presence of an output schema, the description is minimally adequate. However, with no annotations and incomplete behavioral details, it doesn't fully prepare the agent for safe and effective use, especially as a mutation tool.

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 implies the 'text' parameter by stating 'from text,' adding semantic context beyond the schema's 0% coverage. Since there's only one parameter, this minimal addition is sufficient to clarify its purpose, compensating well for the lack of schema descriptions.

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 with a specific verb ('Remove') and resource ('punctuation from text'), making it immediately understandable. It distinguishes from siblings like clean_remove_emails or clean_remove_numbers by specifying punctuation. However, it doesn't explicitly differentiate from all text-cleaning siblings, keeping it from a perfect score.

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. It doesn't mention scenarios where punctuation removal is appropriate, prerequisites, or how it compares to other cleaning tools in the sibling list, leaving the agent without contextual usage cues.

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