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Aayat AI

Translate ($0.01)

translate
Read-only

Translate text between 100+ languages with AI. POST JSON {"text": "...", "target": "French"} (language name or code such as fr, de, es, ja, zh, ar). Optional "source" language, otherwise it is detected. Up to about 12,000 characters of English (4,000 of Chinese/Japanese) per call. Keeps formatting such as Markdown and line breaks. Failed calls are not charged. Price: $0.01 in USDC per call (x402 or prepaid credits). Paid only (not in the free trial).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText to translate.
sourceNoLanguage of the text. Default: detect automatically.
targetYesLanguage to translate into, e.g. French or fr.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
charsYes
modelYes
sourceYesSource language as given, or "auto".
targetYes
translationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations provide readOnlyHint and openWorldHint, but the description adds substantial behavioral detail: 100+ language support, formatting preservation (Markdown/line breaks), character limits per script, failure charging policy, and precise pricing/payment methods. This is rich context beyond annotations.

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 front-loaded with purpose and method, then limits and pricing. It is efficient but slightly dense; all sentences earn their place, though pricing details could be trimmed since the title already includes the price.

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

Completeness5/5

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

Given the simple 3-parameter schema, full schema coverage, presence of an output schema, and informative annotations, the description covers everything an agent needs: purpose, invocation format, limits, formatting behavior, costs, and payment conditions.

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%, so the schema already documents text, source, and target. The description repeats the auto-detect behavior and examples (fr, de, es, ja, zh, ar) but adds only marginal value over the schema's existing examples.

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 opens with a specific verb and resource: 'Translate text between 100+ languages with AI.' It is unambiguous and unique among siblings, so no sibling differentiation is needed.

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

Usage Guidelines4/5

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

Explicit constraints are given: paid-only (not free trial), failed calls not charged, and character limits. However, no alternative translation tools are named, so it falls short of the explicit when/when-not/alternatives pattern.

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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