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get_language_details

Retrieve details for a programming language supported by LLM Sandbox. Pass the language name to get its information for sandbox code execution.

Instructions

Get the details of a language.

Args:
    language: The language to get the details of

Returns:
    TextContent: The details of the language

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
typeYes
_metaNo
annotationsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses only that the result is TextContent, with no information about error handling for unsupported languages, permission needs, or how the language should be identified. This is a thin disclosure for a tool with zero annotation coverage.

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

Conciseness3/5

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

The description is short and the purpose is front-loaded, but the Args/Returns boilerplate conveys almost no information and the parameter line is a tautology. Length is fine; content density is low.

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?

An output schema exists, so return values need not be explained. Even so, for a tool whose only parameter is completely undocumented and which has no annotation coverage, the description is too sparse to let an agent invoke it correctly.

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 description coverage is 0% and the single required parameter is undocumented. The description's 'the language to get the details of' merely restates the parameter name and never specifies whether it expects a language code, name, or locale, so it fails to compensate for the schema gap.

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

Purpose3/5

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

The description states a specific verb and resource ('Get the details of a language'), so the basic action is identifiable. However, it offers no differentiation from the sibling get_supported_languages, and 'details' is vague about what information is actually returned. It is a minimum-viable purpose statement.

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?

There is no guidance on when to use this tool versus get_supported_languages or execute_code, and no prerequisites or context are mentioned. The agent is left to infer usage entirely from the name.

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