Snowflake Cortex Translate

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description restates only that it uses Snowflake Cortex AI, adding no behavioral detail such as latency, token/size limits, cost implications, or whether results are cached.

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 front-loaded sentence with no filler; the operation is stated immediately. It is efficient, though arguably too terse given the gaps in parameter and behavioral coverage.

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?

The presence of an output schema means return values need not be explained, but with three fully required parameters at 0% schema coverage and no annotation gaps being filled, the definition leaves key invocation details (language code format, text constraints) unspecified.

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%, so the description must carry parameter meaning and it does not. It never indicates the expected language format (ISO code vs. full name), whether auto-detect is supported for source_language, or any length limits on text.

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 gives a specific verb (translate) and resource (text) plus directionality (source to target), so an agent knows exactly what operation this performs versus siblings like cortex_summarize or cortex_sentiment. It does not explicitly name a sibling to differentiate against, but the Cortex-family names already do that work.

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 says what the tool does but never says when to choose it over alternatives such as cortex_complete (which could also translate) or when it is inappropriate (e.g., long documents). No prerequisites, no exclusions, no routing guidance at all.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.