get_learning_insights

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

Annotations declare readOnlyHint=true, so safety is already known. The description adds important behavioral context: it discloses what the server tracks (tool calls, failures, latency), what the return fields are (most_used_tools, slowest_tools, error_rate, recommendations), and notes that insights improve with more usage. This goes beyond annotations and schemas. However, it doesn't detail performance characteristics, data retention, or whether insights are per-user or global.

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 front-loaded with the core purpose, then lists return fields in a structured way. It is concise and avoids fluff, though the 'Returns:' section could be considered slightly verbose given an output schema exists. Overall, every sentence earns its place.

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, the description needn't detail return values, but it does provide a helpful summary of them. The description covers what insights are surfaced and how they improve with usage. It might benefit from mentioning whether insights are user-specific or server-wide, but for a read-only analytics tool, it is sufficiently 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?

Parameter count is 0 and schema description coverage is 100%, so baseline is 4. The description correctly implies no inputs are needed. No parameter semantics are relevant here, so the baseline score of 4 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 states a specific verb and resource: 'Show what the server has learned from your QuickSight usage patterns.' It immediately distinguishes itself from all sibling tools by focusing on server-side usage analytics/telemetry rather than QuickSight asset manipulation. No sibling tool is about learning insights from usage patterns.

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 implies the tool is useful for understanding usage patterns and mentions recommendations, but it does not explicitly state when to call it versus alternatives or provide exclusion criteria. The purpose is self-evident enough that a user can infer usage, but there's no guidance like 'call this before optimizing workflows' or 'not for real-time monitoring'.

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