warp_analytics

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

Annotations already declare readOnlyHint=true, confirming read-only nature. Description adds value by detailing what metrics are returned (revenue, shipments, breakdown). No contradictions; no additional behavioral traits needed.

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?

Two sentences, front-loaded with main purpose. No redundant information; every sentence is valuable.

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?

Despite no output schema, description fully explains return values (total revenue, shipment count, breakdown). Given zero parameters and clear sibling differentiation, the description is complete and sufficient.

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?

Input schema has zero parameters (100% coverage), so description correctly adds no parameter info. Baseline 4 for no params; description compensates by explaining the output content.

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?

Description clearly specifies the verb 'Show' and resource 'bookings analytics' with explicit outputs: total revenue, shipment count, breakdown by source. Distinguishes from sibling tools like warp_book, warp_quote_history, etc., which are operational, not analytical.

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?

Provides explicit use case: 'track how much revenue has been generated through AI tools.' No explicit when-not-to-use, but the context of sibling tools makes it clear this is for analytics, not actions like booking or tracking.

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