get_analytics

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

With no annotations provided, the description carries full burden and delivers exceptional transparency. A dedicated section covers side effects (read-only, no side effects), authentication (none for basic), rate limits (free vs pro), error handling (structured errors), idempotency (fully idempotent), and data privacy (local processing). This exceeds 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 well-structured with clear headings and sections, making it easy to scan. However, it is somewhat verbose, repeating details about idempotency and error handling that could be condensed. Overall, good organization but could be more concise.

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 the tool has only 2 optional parameters and an output schema exists, the description covers behavior thoroughly but fails to specify what analytics are produced (e.g., usage counts, trends). The vague reference to 'frameworks or standards' does not clarify the output, leaving a gap in context for an AI agent.

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 0%. The description's 'Args' section provides only generic descriptions ('The period to analyze or process') that add no meaningful meaning beyond the parameter names. No acceptable values, constraints, or examples are given for 'period' or 'api_key' defaults.

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 the tool returns productivity analytics and describes behavior as generating structured output. However, it lacks specificity about what data is returned (e.g., session metrics, trends). This ambiguous purpose is not clearly differentiated from sibling get_sessions, which might provide raw session data rather than analytics.

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 includes explicit 'When to use' and 'When NOT to use' sections, providing clear context for appropriate usage (structured analysis) and caution against real-time decisions without human review. However, it does not directly compare to sibling tools or explain when to choose analytics over session-focused tools.

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