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satish-kori-27

Swedish Language Learning MCP Server

ask_swedish

Ask questions about Swedish vocabulary, grammar, translation, or pronunciation in natural language to get clear answers for language learning. Ideal for voice input and quick study help.

Instructions

Ask any question about Swedish in natural language. Perfect for voice input. Examples: 'How do you say hello?', 'What does kunna mean?', 'Conjugate the verb gå', 'Tell me about Swedish pronunciation'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYesYour question about Swedish language in natural conversational form

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden, and it discloses only that input is natural conversational language suited to voice. It says nothing about response format, latency, confidence, or limitations of the 'any question' claim. The voice/natural-language note is genuine added context, but far from complete for a QA tool.

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?

Purpose is front-loaded in the first sentence, followed by a usage hint and four compact examples. No filler, though the example list is slightly longer than needed to convey the tool's breadth.

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

Completeness3/5

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

For a one-parameter, low-complexity tool with full schema coverage and no output schema, the description is adequate. Its main gap is contextual: with five overlapping siblings, it never clarifies when this general-purpose asker should be preferred over grammar_help or translate_swedish.

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

Parameters3/5

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

Schema description coverage is 100% for the single 'question' parameter, so the schema already documents its type and conversational form. The examples add a little color about what shapes a question can take, but nothing beyond what the schema conveys; baseline 3 applies.

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

Purpose4/5

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

The description states a specific verb and resource ('ask any question about Swedish') and the examples concretize the domain (translation, definitions, conjugation, pronunciation). However, it never distinguishes itself from siblings like grammar_help, translate_swedish, or get_vocabulary, which the examples clearly overlap with, so an agent cannot route confidently from the description alone.

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

Usage Guidelines3/5

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

'Perfect for voice input' implies a usage context (spoken/natural-language queries), which is a real hint. But there is no explicit when-to-use/when-not-to-use guidance and no named alternative for cases better served by grammar_help or translate_swedish, so the routing decision is left to inference.

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