get_study_insights

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

With no annotations provided, the description carries the full burden. It discloses a key behavioral trait: analytics must be generated first, and directs the user to get_analytics_status if components are missing. The 'Get' verb implies a read operation, though it doesn't explicitly state that no mutation occurs. This is more transparent than typical descriptions.

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 well-structured and front-loaded with the purpose, then usage triggers, alternatives, and a prerequisite warning. Every sentence earns its place; no fluff or repetition exists.

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 tool with one parameter and an output schema, the description covers the purpose, when to use, alternatives, and necessary prerequisites. The dependency on generated analytics is clearly explained, making the tool's context fully complete.

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 only one parameter, study_id, with no property description (0% schema coverage). The description's Args section provides a minimal explanation: 'The unique identifier of the study.' This adds only slightly more meaning than the parameter name itself, so it barely compensates for the missing schema-level description.

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 tool's function: 'Get overall and per-section insights for a study, including key findings and actionable recommendations.' This is a specific verb+resource combination that distinguishes it from siblings like get_analytics_summary and get_study_report.

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 explicitly tells when to use the tool: when the user asks 'what should we fix', 'what are the main issues', or wants prioritized action items broken down by section. It also names alternatives: get_analytics_summary for a shorter executive summary, and generate_study_report + get_study_report for a full combined report. The prerequisite workflow with get_analytics_status and generate_analytics adds clear usage guidance.

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