snowflake_cortex_sentiment

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It only states the output range and does not mention safety, side effects, limits (e.g., input length, language support), or error conditions. For a read-only analysis tool, this is minimal; it does not reveal potential pitfalls or operational characteristics an agent might need.

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 a single, clear sentence that states the action and the output. There is zero redundancy, and the essential information is front-loaded. It is appropriately sized for a tool with a single parameter and a well-defined return.

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?

Given that an output schema exists (though its contents are not shown here) and the tool is simple, the description is adequate for a basic call. However, it lacks context on any prerequisites, input limits, or whether the tool handles non-English text. It is not incomplete enough to make the tool unusable, but it leaves some operational questions unanswered.

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 has one parameter 'text' with no description (0% coverage). The tool description says 'Analyze sentiment of text', which adds no information beyond the parameter name itself—it does not clarify expected format, length constraints, or encoding. Since the schema provides nothing, the description should compensate but fails to add meaningful detail about the 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 clearly states the verb 'Analyze', the resource 'text', and the output as a sentiment score ranging from -1.0 to 1.0. It is specific and distinct from all sibling tools, which focus on data management, queries, or other Cortex capabilities. The output range precisely defines what the tool does.

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 provides no explicit guidance on when to use it versus alternatives like snowflake_cortex_summarize or snowflake_cortex_extract_answer. An agent can infer it is for sentiment analysis, but there is no mention of when it is appropriate or any exclusions. It is straightforward but leaves usage context to the agent's discretion.

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