Run a deep-dive analytics investigation

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior. The description adds the aggregation trait (seven reads composed in one call) and notes the forecast is point-in-time, which is real context beyond the annotations, though it stops short of describing rate limits or auth requirements.

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?

Front-loaded with the core purpose, then differentiation, then a worked example. The seven-item enumeration is dense but each entry earns its place by defining the tool's scope; the text is slightly heavy but never wasteful.

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?

With an output schema present, return values need no explanation, and the annotations carry the safety profile. The description covers scope, aggregation behavior, differentiation, and an example, leaving nothing an agent needs in order to call it correctly.

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 100%, so the schema already documents period, question, workspaceId, and workspaceSlug. The description's example shows period and question usage but adds no syntax or semantics the schema lacks, making the baseline 3 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?

States a specific verb and outcome ('Answer a specific business question by composing all seven analytics reads in one call') and then enumerates exactly which reads are included. It explicitly distinguishes itself from luca_analytics_magic_monday, so an agent can separate the two without opening a schema.

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?

Names the alternative (luca_analytics_magic_monday) and the condition that selects this tool instead: when the coach asks a specific question needing cross-referencing several numbers. The concrete example call reinforces when and how to invoke it.

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