get_analytics

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

With no annotations provided, the description takes full responsibility. It clearly states 'Read-only — never calls an LLM, never writes to disk,' which is a critical safety disclosure. It also details the cumulative nature of report types and the uninitialized fallback behavior, going far beyond basic expectations.

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 long but efficiently structured: it leads with purpose and safety, then lists report types with their exact return shapes, and ends with the uninitialized case. Every sentence carries necessary information without repetition or fluff.

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 three optional parameters with rich enums, no output schema, and complex behavior, the description is exceptionally complete. It covers return values for every report type, the cumulative relationship, and an edge case (uninitialized). This is a model description for a complex diagnostic 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?

Although schema coverage is 100%, the description adds significant semantic value: it explains exactly what each report_type returns, how time_range is ignored for some types, and the cumulative relationship of report types. This provides practical understanding that raw schema enums cannot convey.

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: 'Inspect SAB's internal telemetry' and enumerates concrete data categories. This clearly distinguishes it from sibling tools like review or ask, which are about coding actions rather than diagnostics.

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 when-to-use guidance is given: 'Use to diagnose why SAB picked backend X, tune routing rules, or understand cost trade-offs.' It does not mention when not to use or alternatives, but the tool's unique role among siblings makes this implicit.

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