Detect the language of input text and translate it to any specified target language. Cost: $0.01 USDC via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Target language name (e.g. 'Japanese', 'French', 'Spanish') | |
| text | Yes | Text to translate |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations include 'destructiveHint: true', but the description does not explain why it is potentially destructive (e.g., cost implications or state changes). The only behavioral note is 'Cost: $0.01 USDC via x402.', which addresses some external consequence but not destruction. No contradiction, but significant gap given the annotation.
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 very concise with two sentences. It front-loads the main action and includes cost information. However, it omits usage guidelines and behavioral details, which would improve it.
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 2-parameter tool with no output schema, the description lacks explanation of return values or format. With no output schema, the agent needs to know what the tool returns. Still, the core purpose is clear.
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 description coverage is 100%, and the description adds no further semantics beyond what the schema already provides. 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 states 'Detect the language of input text and translate it to any specified target language.' This gives a clear verb (detect and translate) and resource (input text), and the name implies support for any target language, distinguishing it from sibling tools like 'interzoid_translate_to_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 does not provide guidance on when to use this tool versus alternatives like 'interzoid_identify_language' or 'interzoid_translate_to_english'. It only states what it does, not when to choose it over siblings.
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.
