AI translation to 11 locales, MDX-aware (preserves code blocks and URLs). 50 sats per call.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to translate | |
| format | No | Input format (default: plain) | |
| locale | Yes | Target locale (e.g. es, zh, ar, pt, fr, de, ja, ko, hi, ru, it) |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the key behaviors: AI-powered translation, preservation of code blocks/URLs when MDX-aware, and a per-call cost of 50 sats. This gives the agent a solid understanding of side effects and resource usage. It stops short of mentioning rate limits or error behavior, but for a translation tool these are minor gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, 15 words, front-loaded with the core action and target, then adding the differentiator and cost. Every element earns its place; no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 3 parameters and no output schema, the description covers the main purpose, the MDX handling, and the cost. It does not specify the source language assumption or character limits, but these are not critical for basic invocation. The presence of the schema and the description together make the tool sufficiently complete for an agent to select and call it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all three parameters with descriptions (100% coverage), so the baseline is 3. The description adds value by clarifying the 'format' parameter's purpose ('MDX-aware (preserves code blocks and URLs)') and specifying the locale count, which reinforces the 'locale' parameter's valid values. This elevates the semantic clarity beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('AI translation') and resource ('11 locales'), clearly distinguishing it from the sibling tools which cover pricing, scraping, search, etc. It also adds a distinctive capability (MDX-aware) that further clarifies its purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: translate to 11 locales, with MDX support for preserving code blocks and URLs. It implies when to use it (any translation need) and hints at format behavior, but does not explicitly discuss alternatives or when not to use it. Since no sibling tool is a translation service, the intended usage is unambiguous.
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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