cortex_translateTranslates text between languages using Snowflake Cortex AI. Provide source text, source language, and target language to get translated output.
Translate text from a source language to a target language using Snowflake Cortex AI.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| source_language | Yes | ||
| target_language | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v2.0.4Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds essentially nothing beyond that: no note on supported language identifiers, model behavior, rate limits, or failure modes from Cortex.
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?
A single, well-formed sentence with the core action front-loaded and no filler. It is efficient, though its brevity comes at the cost of the missing semantics noted elsewhere.
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?
An output schema exists, so return values need not be explained. However, for a 3-required-parameter tool with zero schema descriptions, the language-code format and any constraints on the text input are left entirely unspecified, leaving an agent guessing on the fields most likely to cause an incorrect call.
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 0% across all three required parameters, so the description carries the burden. It restates the field names conceptually but never specifies the expected language format (e.g. ISO/BCP-47 codes like 'en' vs 'English') or how empty/unsupported language values behave.
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 (translate) and resource (text), plus the scoping detail that it runs on Snowflake Cortex AI. It is clearly distinguishable from siblings like cortex_summarize or cortex_sentiment, though it does not explicitly name an alternative.
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?
There is no when-to-use guidance, no mention of prerequisites, and no routing to sibling tools. An agent can infer the purpose but gets no help deciding between this and, say, cortex_complete for a translation-style task.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.