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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds genuinely non-inferable behavior: the empty-until-first-monthly-read state and the workspace entitlement gate, both of which prevent false-negative interpretation of an empty result. The category definitions also explain what the classification means rather than just naming it.

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 resource then the three category definitions in parallel structure, each of which earns its place by teaching the agent how to act on the output. Slightly dense and fragment-like in the opening sentence, and the workspace restriction trails at the end where it could be promoted.

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 only two optional parameters, a full output schema, and complete annotations, the remaining descriptive burden is precisely preconditions and category semantics — both covered. The one gap is that windowing behavior relative to `days` is left to the schema, which is acceptable given 100% coverage.

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 coverage is 100%, with both `days` (enum, default 30) and `workspaceId` fully documented in the schema, so the baseline is 3. The description adds nothing about the reporting window or how it interacts with the categories; the mention of a 'monthly read' cadence is the only adjacent signal but does not explain the `days` enum.

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 opening line establishes the resource (tracked questions) and the organizing axis (how open they are before a model searches), and the three category labels are defined concretely enough that an agent knows what it gets back. It stops short of stating the return shape as a sentence and does not differentiate itself from near-neighbors like readDecaying, readOpportunities or readFanoutGaps, so an agent must infer which winnability read it wants.

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?

Gives a decisive action rule ("Write for winnable questions first") plus an explicit precondition ("Only for a workspace that tracks its AI visibility ... has tracked prompts") and a freshness caveat ("Empty until the first monthly read"). It names no alternative sibling or when-not-to-use case, so the routing is clear but not exhaustive.

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