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Detect Language

detect_language

Detect the language of a piece of text - free, no payment. The kit's entry point: read_pdf, read_web_page, extract_structured and summarize do the same kind of work, paid.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Added

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description bears the behavioral transparency burden. It adds the cost-related trait 'free, no payment,' which is useful, but it does not disclose whether the tool is read-only, how it handles ambiguous or empty input, or what form the result takes. The 'kit's entry point' phrase adds little concrete behavior.

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

Conciseness2/5

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

The first sentence is appropriately concise, but the second sentence is off-topic, grammatically awkward, and does not earn its place. It confuses rather than clarifies, and it does not support tool selection or invocation.

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 detection tool with an output schema, the description covers the basic input and free access. However, the misleading sibling sentence and lack of clarity about what counts as 'same kind of work' leave the context incomplete for an agent choosing among siblings.

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 provides only 'text' as a string with 0% coverage, so the description must compensate. 'Detect the language of a piece of text' does clarify that the text parameter is the content whose language should be detected, but it adds no constraints, examples, or edge-case guidance.

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 first sentence, 'Detect the language of a piece of text,' clearly states the verb, resource, and scope. However, the second sentence muddies sibling differentiation by claiming read_pdf, read_web_page, extract_structured, and summarize do 'the same kind of work,' which is inaccurate and confusing.

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 mentions that this tool is free and that other tools are paid, but it never states when to use this tool versus its siblings. There is no explicit condition, task context, or when-not-to-use guidance, so an agent gets no actionable routing.

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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