backlinks_timeseries_new_lost_summary

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 describes what the tool returns (counts of new/lost backlinks and referring domains) and the grouping behavior. However, it doesn't mention important behavioral aspects like whether this is a read-only operation, potential rate limits, authentication requirements, data freshness, or what happens when no data exists for certain periods (though the schema mentions returning 0).

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 appropriately sized with three sentences that each serve a purpose: stating what the tool provides, describing the time parameters, and explaining the primary use case. It's front-loaded with the core functionality. While efficient, the third sentence could be slightly more concise by integrating the use case context earlier.

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 the tool's moderate complexity (time-series analysis with grouping), no annotations, and no output schema, the description provides adequate but incomplete context. It explains what metrics are returned and their use case, but doesn't describe the output format, potential limitations, or how to interpret the results. For a time-series tool with no output schema, more detail about the return structure would be helpful.

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 100%, so the schema already documents all four parameters thoroughly. The description adds minimal value beyond what's in the schema - it mentions the target field and date range parameters but doesn't provide additional semantic context. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 specific action ('provide you with the number of new and lost backlinks and referring domains'), resource ('for the domain specified'), and scope ('for a period between the two indicated dates, and metrics will be grouped by the time range'). It distinguishes from sibling tools like 'backlinks_summary' or 'backlinks_timeseries_summary' by focusing specifically on new/lost metrics for time-series analysis.

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 explicitly states when to use this tool: 'Data from this endpoint will be especially helpful for building time-series graphs of new and lost backlinks and referring domains.' This provides clear context about its primary use case. However, it doesn't explicitly mention when NOT to use it or name specific alternatives among the many sibling tools.

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