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 but lacks details such as whether the removal is destructive (e.g., strips tags leaving plain text), handles nested tags, or preserves text content. This is a significant gap for a tool with potential side effects.

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 zero waste—it states the core function without fluff. It's appropriately sized for a simple tool and front-loaded with the essential action.

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 parameter) and the presence of an output schema, the description is minimally adequate. However, without annotations and with incomplete behavioral context, it leaves gaps in understanding how the tool behaves, such as error handling or output format details.

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 is the input from which HTML tags are removed, adding meaning beyond the schema's 0% coverage. Since there's only one parameter, this is sufficient to understand its role, though it doesn't specify format constraints (e.g., if it expects raw HTML strings).

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 verb ('Remove') and resource ('HTML tags from text'), making the purpose immediately understandable. It distinguishes from siblings like clean_remove_emails or clean_remove_urls by specifying HTML tags. However, it doesn't explicitly contrast with other text cleaning tools beyond the name, 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?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention if it's for preprocessing text before analysis or how it differs from other cleaning tools like clean_remove_punctuation. This leaves the agent without context for selection among siblings.

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