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 action ('Count words') but does not explain how words are defined (e.g., handling of punctuation, numbers, or whitespace), what the output looks like, or any limitations such as text length constraints. This leaves significant 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, direct sentence with zero wasted words, making it highly concise and front-loaded. Every word earns its place by conveying the core purpose efficiently without unnecessary elaboration.

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 (a simple counting operation) and the presence of an output schema (which should document return values), the description is minimally adequate. However, with no annotations and incomplete parameter semantics, it lacks sufficient context for reliable use, especially compared to detailed siblings in the suite.

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 input schema has 1 parameter with 0% description coverage, and the tool description does not add any semantic details about the 'text' parameter. It does not clarify what constitutes valid text input, examples, or constraints, failing to compensate 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 'Count words in text' clearly states the verb ('Count') and resource ('words in text'), making the purpose immediately understandable. However, it does not differentiate from siblings like 'count_paragraphs' or 'count_sentences', which perform similar counting operations on different text units, so it lacks sibling distinction.

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 siblings like 'count_paragraphs' and 'count_sentences' available, there is no indication of context, prerequisites, or exclusions for choosing this tool over others in the text analysis suite.

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