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blackmount-nlp-mcp

blackmount-nlp-mcp

by BlackMount-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

extract_rake_keywords

Extract multi-word key phrases from text using the RAKE algorithm. Identify top topics by specifying the number of keywords to return, with a default of 10.

Instructions

RAKE keyword extraction (Rapid Automatic Keyword Extraction). Finds multi-word key phrases.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>"
    },
    "name": "extract_rake_keywords"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes
top_nNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, and the description does not disclose any behavioral traits such as language support, processing speed, or limitations (e.g., performance on short texts).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise (two sentences) and front-loads the acronym. While efficient, it sacrifices necessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and no explanation of output schema, the description is incomplete. It doesn't mention language requirements, stopword handling, or return value format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description does not explain the 'text' or 'top_n' parameters. The default for top_n is given in the schema but not explained in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool extracts RAKE keywords, expands the acronym, and specifies it finds multi-word key phrases. This distinguishes it from sibling tools like extract_tfidf_keywords.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no indication of when to use RAKE vs alternative keyword extraction methods (e.g., TF-IDF). No context on prerequisites or ideal use cases.

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

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