translate-doc
PREMIUM: translate a long document into any language. input='en | '. [x402: 0.05 USDC on Base, pay-per-use]
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | '<idioma_destino> | <documento>' |
PREMIUM: translate a long document into any language. input='en | '. [x402: 0.05 USDC on Base, pay-per-use]
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | '<idioma_destino> | <documento>' |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the full burden and does well by disclosing the pay-per-use cost via '[x402: 0.05 USDC on Base].' It does not describe output characteristics or failure cases, but for a translation call the pricing disclosure is the main behavioral risk.
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 packs purpose, input format, and cost into a single compact line with no waste. The PREMIUM label is front-loaded, and the pricing detail is cleanly isolated.
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 one-parameter tool with full schema coverage, this is complete: it states what is translated, how to format the input, and what financial consequence the call carries. The output schema is absent, but a translation tool's output is evident from its purpose.
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 schema already documents the input as '<idioma_destino> | <documento>' with 100% coverage, so the baseline is 3. The description adds a concrete worked example ('en | <long text>') that reinforces the pipe-delimited order and clarifies the target-language parameter.
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 uses a clear verb+resource pair, 'translate a long document into any language,' and immediately makes the scope concrete with an example input format. This distinguishes it from siblings like translate-to or translate-en by emphasizing the long-document and premium positioning.
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?
It explicitly positions the tool for long-document translation, which gives a clear context for when to choose it. It does not explicitly mention lighter alternatives like translate-to for short text, so it falls just short of full when/not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The set contains many trivially indistinct tools: ai-inference/inference, compress/comprimir, count-tokens/contar-tokens, detect-language/language-detect, and multiple overlapping OCR receipt variants. With 160 tools and pairs that differ only by language or suffix, an agent cannot reliably distinguish several capabilities.
Most names are readable lower-hyphen identifiers, but they mix action verbs, noun phrases, domain prefixes, pipeline suffixes, Spanish/English, and arbitrary demo/batch labels. There is a loose convention, but no consistent verb_noun pattern.
160 tools on one server is an extreme count and clearly unwieldy. Even as a marketplace, exposing every variant, demo, and composed bundle as a top-level MCP tool overwhelms agent selection and adds little distinct capability.
The set covers a huge range of text, image, audio, code, market, compliance, and content-workflow tasks, so many intents have some available tool. However, it is a grab-bag rather than a defined service surface, and the arbitrary demo/specialized variants make it unclear whether a needed operation truly exists or is just a duplicate.