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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns coverage/perimeter metadata rather than findings, and warns of incompleteness by design. It stops short of saying whether results are cached, how fresh they are, or whether counts are approximate.

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 tight sentences: first defines what is returned, second gives the calling condition. Front-loaded and waste-free, though a slightly more explicit link to the sibling data tools could be fitted without bloat.

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 zero-param, no-annotation metadata tool, the description covers purpose and calling conditions well. With no output schema, it could say more about the shape of the response (counts vs percentages), which is the one real gap.

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?

Zero-parameter tool, which is the baseline-4 case. The description needs no parameter explanation, though it could note that coverage is global and cannot be scoped to a single brand or show, which matters if a caller wants per-entity percentages.

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 resource (dataset coverage) and enumerates what it reports: shows indexed, episodes transcribed, brand and show counts with detected ad reads. Clearly distinct from data-returning siblings like get_brand_podcasts.

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?

Explicitly says when to call it ('before stating any sponsor finding as complete') and what it's for ('explain why a show or brand might be missing'). That's a named precondition plus a diagnostic use case, with no ambiguity.

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