Detect the language of input text and translate it to English. AI-powered translation supporting numerous world languages. Cost: $0.01 USDC via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text in any language to translate to English |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations include destructiveHint=true and openWorldHint=true. The description adds 'AI-powered' and cost '$0.01 USDC via x402', but does not explain why the tool is marked destructive or what side effects exist. Some additional context beyond annotations, but insufficient depth.
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?
Description is three short sentences, front-loaded with the core purpose. No unnecessary words or repetition. Efficiently conveys purpose, capability, and cost.
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 one required param and no output schema, the description covers detection, translation, and cost. It does not detail output format, but that is acceptable given the tool's straightforward nature. Slightly missing context about supported languages or use of external API.
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?
Schema coverage is 100% with the 'text' parameter described as 'Text in any language to translate to English'. The description adds no new semantics beyond the schema, so baseline 3 is appropriate.
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 clearly states the tool detects language and translates to English ('Detect the language of input text and translate it to English'). It distinguishes from sibling 'interzoid_translate_to_any' by specifying translation target as English.
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 implies usage for translating to English, but does not explicitly state when to use this vs. 'interzoid_translate_to_any' or any exclusions. The sibling list provides contrast but the description lacks direct 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.
Most tools target distinct data operations (matching, standardization, enrichment) with clear descriptions. Minor overlaps exist, e.g., address_match_advanced vs global_address_match, but descriptions differentiate them.
All tools follow a consistent 'interzoid_descriptive_function' pattern in snake_case, making it easy to predict purpose from the name.
58 tools is high for a single server, exceeding the typical 3-15 range. While each serves a specific data enrichment function, the quantity may overwhelm agents without clear categorization.
The tool surface covers a broad domain including address, company, person, and financial data. Minor gaps exist (e.g., no reverse IP lookup, limited social media coverage), but core data needs are well-addressed.
