Read objection patterns

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

Annotations already cover readOnly/idempotent/non-destructive, but the description adds real value beyond that: required scopes (analytics:read, luca:read), data sensitivity (full_content), workspace override behavior, and the notable empty-state expectation ('never fabricated'). It stops short of rate limits or pagination behavior.

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 purpose is front-loaded in the first sentence with the key output fields, followed by a compact metadata block (operation, scopes, idempotency, workspace override). Slightly dense but every line carries actionable information.

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?

For a read-only analytics rollup with an output schema present, the definition covers scope, auth requirements, sensitivity, and the semantics of an empty result. Nothing critical to invoking it correctly appears to be missing.

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 67%, and the description compensates by explaining that period governs the rollup window, that channel is a filter, and that workspaceId/workspaceSlug override the environment-configured default. It does not add format or default-value detail beyond the schema's enums.

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 names a specific resource (objection-bucket rollup over review-queue qualifier signals) and enumerates the exact buckets and output metrics, so the agent knows precisely what it returns. It does not explicitly name or contrast the closely-named sibling luca_analytics_objection_drilldown, so sibling differentiation is only implicit through 'rollup'.

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?

It gives a filter condition ('Filter by channel') and workspace override guidance, which implies usage context for an analytics read. However there is no explicit when-to-use/when-not guidance and no routing toward alternatives such as the drilldown variant.

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