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ctkadvisors

GraphQL MCP Server

by ctkadvisors

language

Query and retrieve language data using a GraphQL API. Input a code parameter to access specific language information efficiently.

Instructions

GraphQL language query

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYescode parameter (ID)
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure but provides minimal information. 'GraphQL language query' suggests a read operation but doesn't specify if it's safe, what permissions might be required, what format the response takes, or any rate limits. It doesn't disclose whether this queries language data or executes GraphQL operations, leaving significant behavioral uncertainty.

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 extremely concise at just three words, which could be appropriate if it were more informative. However, the brevity comes at the cost of clarity - it's under-specified rather than efficiently informative. The structure is simple but doesn't effectively front-load the most critical information.

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 tool has no annotations, no output schema, and a minimal description, the contextual information is insufficient. For a tool with one required parameter that presumably returns language data (based on sibling tools), the description should explain what the tool returns, how it relates to the 'languages' sibling, and what the 'code' parameter represents beyond just being an ID.

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?

The schema has 100% description coverage, with the single parameter 'code' documented as 'code parameter (ID)'. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in description, which applies here.

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

Purpose2/5

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

The description 'GraphQL language query' is tautological - it essentially restates the tool name 'language' with the addition of 'GraphQL query'. It doesn't specify what the tool actually does (e.g., retrieves language information, validates language codes, etc.) or what resource it operates on. While it mentions 'GraphQL', it doesn't clarify if this executes a GraphQL query or returns GraphQL schema information about languages.

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

Usage Guidelines1/5

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 its siblings (continent, continents, countries, country, languages). There's no indication of what differentiates this language tool from the 'languages' sibling tool, nor any context about appropriate use cases, prerequisites, or alternatives.

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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