blackmount-nlp-mcp

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the transformation ('collapse multiple whitespace into single spaces') but doesn't cover aspects like whether it's idempotent, handles edge cases (e.g., tabs or newlines), or what happens with leading/trailing spaces. This leaves gaps in understanding the tool's behavior.

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, efficient sentence that directly states the tool's function without any wasted words. It's front-loaded and appropriately sized for a straightforward tool.

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 (1 parameter, no annotations, but with an output schema), the description is minimally complete. It explains the core transformation but lacks details on behavior and usage context, which could be important for an AI agent to invoke it correctly alongside 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?

With 0% schema description coverage and only 1 parameter, the description implies the parameter's purpose ('text' to be processed) but doesn't add detailed semantics beyond the schema's title. However, the simplicity of the tool (single input) means the description is adequate, though not rich in parameter details.

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 ('collapse') and resource ('multiple whitespace into single spaces'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'clean_text_pipeline' or other cleaning tools, which could handle similar transformations.

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, such as other cleaning tools in the sibling list (e.g., 'clean_remove_punctuation' or 'clean_text_pipeline'). There's no mention of specific contexts, prerequisites, or exclusions for usage.

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