gsc_content_decay

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly instructs to base analysis only on returned data, report exact numbers, avoid speculation about causes, and acknowledge insufficient information. It also mandates a specific presentation style (rich, interactive visualization with artifacts, summary cards, colour-coded indicators, etc.), giving the agent clear expectations for behavior and output.

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 description is longer than average but well-structured: it starts with the core purpose, then adds behavioral constraints (IMPORTANT) and presentation requirements (PRESENTATION). The sentences are purposeful and not wasteful. However, the caps-lock section headers and detailed presentation instructions could be seen as slightly verbose, though they earn their place given the lack of an output schema.

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?

Given that there is no output schema and no annotations, the description thoroughly compensates. It explains what the tool identifies, the criteria, the analytical constraints (data fidelity, no speculation), and the required presentation format. It is complete enough for an agent to invoke and produce the expected result without additional clues.

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?

The input schema has 100% coverage for the single 'dataset' parameter, which is documented as 'BigQuery dataset containing GSC data.' The description does not add additional meaning about this parameter (e.g., format, defaults, requiredness), so it provides no value beyond the schema. Baseline 3 is 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?

The description states a specific verb and resource: 'Find pages with consistent traffic decline over three consecutive months from GSC bulk export data.' It adds a clear criterion ('One bad month is noise; three is a problem') that distinguishes this from related tools like gsc_traffic_drops or gsc_anomalies, making the purpose unambiguous.

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?

The description clearly implies when to use this tool: when there is a need to identify sustained declines over multiple months. It does not explicitly name alternative tools or state when not to use, but the three-consecutive-months criterion provides strong contextual guidance that differentiates from sibling tools.

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