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

Annotations already establish that this is a read-only, non-destructive operation. The description adds useful behavioral context by documenting the minimum-completes requirement and the nature of the output, which is beyond what annotations convey. It could also mention behavior when the threshold is not met, but the added prerequisite is meaningful.

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, focused sentence that front-loads the core purpose (AI digest of results) and immediately appends the output components and the key prerequisite. Every element earns its place; there is no filler or redundancy.

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 single-parameter, read-only tool, the description provides sufficient context: it names the output content, states the threshold, and the schema fully documents the input. Since there is no output schema, the description does not detail the exact return structure, but it still gives an agent enough information to decide whether and how to call the tool.

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 survey_id parameter is already well-documented with type, minimum, and guidance to list_surveys or create tools. The tool description mentions 'results' but adds no additional meaning to the parameter itself, so the baseline score of 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 clearly identifies the tool as producing an AI-written digest of results and specifies the content categories: headline, key points, and watch-outs. It is distinct from sibling tools like get_results or get_insights_report by signaling an AI-generated, synthesized summary, though it does not explicitly name or contrast those siblings.

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 tool includes an important precondition ('needs ≥3 accepted completes'), which gives the agent a concrete condition for when the tool is callable. However, it does not explicitly state when to prefer this tool over get_results, get_insights_report, or get_launch_summary, nor does it describe any when-not-to-use scenarios.

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