gsc_diagnose_traffic_drop

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

Annotations already declare read-only, open-world, idempotent, and non-destructive behavior. The description adds a valuable behavioral note that results are 'evidence, not causal attribution,' which helps set expectations about the output's interpretative nature. This goes beyond what annotations provide, though it doesn't cover other traits like pagination or rate limits.

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 two short sentences. The first sentence front-loads the primary purpose, and the second adds a necessary caveat. It is concise, clear, and without filler.

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?

There is no output schema, so the description should partially explain what to expect. It mentions result categories (pages, queries, countries, devices) but does not describe the output format, pagination, or how results are sorted. The 'evidence not causal' note adds context but overall the description leaves moderate gaps for a tool with 8 parameters and no output schema.

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 only 13%, leaving most parameters without explanatory text. The description does not elaborate on any parameters (e.g., date ranges, type, dataState). It only implies 'period-over-period' through the concept, but does not map to the specific date parameters. The description fails to compensate for the low schema coverage.

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 clearly states the tool's purpose: finding pages, queries, countries, and devices with the largest period-over-period traffic declines. It uses a specific verb ('Find') and resource scope, distinguishing it from sibling tools like gsc_query_pages or gsc_compare_periods.

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 implies a clear usage context: diagnosing traffic drops by identifying declining dimensions. The caveat 'Results are evidence, not causal attribution' provides important context about how to interpret results. However, it does not explicitly mention alternatives or when not to use this tool, so it falls short of a 5.

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