get_analytics_status

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

With no annotations, the description carries the transparency burden. It discloses the 2-5 minute generation time, the concept of 'stale' components, and implies a non-destructive status check. It does not explicitly state whether it is read-only, but the context makes this clear.

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?

Well-structured with a clear purpose statement, actionable decision bullets, and a short args section. Every sentence earns its place, with no redundant or filler content.

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 one-parameter status-check tool with an output schema, the description provides a complete decision workflow, including when to use it, what it returns, and how to proceed. It covers all necessary context for an agent to invoke it correctly.

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?

Only one parameter, study_id, is described as 'the unique identifier of the study'. This adds minimal meaning beyond the schema field name. Since schema description coverage is 0%, the description partially compensates, but the parameter is simple and self-explanatory.

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 uses a specific verb 'Check' and resource 'what analytics have been generated for a study', and lists the components (qual, quant, QnA, summary, insights, report). It clearly distinguishes itself from sibling read tools by being a status gate before generation.

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?

Explicit usage guidance is given: if all needed components are present, call read tools directly; if missing or stale, call generate_analytics first (with time estimate). It also instructs to always call this before generate_analytics to avoid unnecessary work.

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