query

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

No annotations provided, so description carries full burden. It discloses that date keywords are resolved in the site's timezone, which is useful. However, it does not mention auth requirements, rate limits, error handling, or the impact of running raw queries. For a powerful tool, more behavioral context would be expected.

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 sentences with no extraneous information. Front-loaded with purpose and specific examples. Every sentence adds value.

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?

No output schema, so description should hint at return format or behavior. It does not mention what the query returns or how to interpret errors. For a tool with 8 parameters and nested objects, more completeness would be helpful, but the description is adequate for its core purpose.

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 75%, so description adds value beyond schema. It explains the date_range parameter in detail, including friendly keywords and timezone resolution. Other parameters (e.g., metrics, dimensions) are not elaborated beyond what the schema provides. Baseline 3 is appropriate because description adds some value but not comprehensive.

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?

Description clearly states it runs a raw Plausible Stats API v2 query for scenarios not covered by other tools. It lists specific use cases (custom property breakdowns, multi-dimension + time series, comparisons, imports, behavioral filters), distinguishing it from siblings like get_breakdown or get_timeseries.

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 to use for 'anything the other tools don't cover' and provides examples, implying when to choose this over siblings. Lacks explicit when-not-to-use or prerequisites, but the context of sibling tools and the phrase 'for anything the other tools don't cover' gives clear guidance.

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