Cortex Extract Answer

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=true, so the safety and determinism profile is covered by structured data. The description adds only the 'direct answer' framing (extraction vs. generation), but says nothing about model behavior, grounding, latency, or input size limits. With annotations carrying the main burden, this is adequate but thin.

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 or redundancy. It is efficient, though arguably too terse for a tool with zero schema documentation.

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. But for an open-world Cortex AI function with no schema descriptions and no usage routing against its many Cortex siblings, the description leaves real gaps for correct invocation.

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 schema itself documents nothing. The description partially compensates by naming both concepts — 'question' and 'unstructured source document/text' — which map onto the two required parameters. It still omits format details such as whether source_text is raw text or a document reference and any size constraints.

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?

States a specific verb+resource: extract a direct answer to a question from unstructured source text. This is clearly distinguishable from mutation siblings like queries_execute_dml. However, it does not distinguish itself from the closest Cortex AI siblings (cortex_complete, cortex_search), so it stops short of a 5.

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 prerequisites, and no mention of alternatives such as cortex_search or cortex_complete for related NLP tasks. The agent must infer from the name alone when this tool is the right pick.

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