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 states the basic operation but lacks details on behavior such as how blank lines are defined (e.g., handling multiple blank lines, whitespace), whether it's case-sensitive, or what the output format is. The description is minimal and doesn't cover key behavioral aspects.

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 with zero waste. It front-loads the purpose and includes necessary detail about paragraph separation, making it appropriately sized and well-structured for its simplicity.

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 has an output schema), the description is minimally adequate. It covers the basic operation but lacks details on behavior and usage context. The output schema likely handles return values, so the description's gaps are less critical, but it could be more informative.

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?

There is 1 parameter with 0% schema description coverage. The description adds meaning by specifying that paragraphs are separated by blank lines, which clarifies the 'text' parameter's expected content and formatting. This compensates well for the lack of schema details, though it could mention text encoding or length limits.

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 ('Count') and resource ('paragraphs in text'), specifying that paragraphs are separated by blank lines. It distinguishes from siblings like count_sentences and count_words by focusing on paragraphs, though it doesn't explicitly contrast with them.

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 like count_sentences or count_words. The description mentions paragraph separation by blank lines, which implies usage for that specific formatting, but doesn't state when to prefer it over other counting tools.

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