Smart Stats

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

The annotations only declare readOnlyHint and openWorldHint. The description adds valuable behavioral details: automatic defaults, validation, post-processing, auto-pagination across pages, the 366-day date range constraint, cursor-driven manual pagination, and a list of broken scopes. This significantly exceeds what the annotations convey.

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 structured with line breaks and category headers, making it scannable. The first sentence front-loads the core purpose. Some content, such as the exhaustive scope list, is necessary for correct tool selection and could not be easily trimmed without losing 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?

Given the tool's complexity (10 parameters, many scope options) and the absence of an output schema, the description does a solid job explaining behavior, pagination, and constraints. It covers return-related concepts like rows and nextCursor, though it doesn't fully describe the response shape. Still, it provides enough context for an agent to choose and invoke the tool correctly.

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 already covers all 10 parameters with descriptions (100% coverage), so the baseline is 3. The description goes beyond by grouping scopes by category, calling out broken scopes, explaining when to use granularity 'none', and showing how to use the cursor with nextCursor. These additions give real semantic value beyond the schema.

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 opening sentence states a specific action: 'Retrieve Gorgias analytics with automatic defaults, validation, post-processing, and auto-pagination.' It clearly identifies the resource (Gorgias analytics) and distinguishes itself from the raw sibling tool by explicitly directing raw API needs to gorgias_retrieve_reporting_statistic. The scope categories further clarify what kinds of analytics are included.

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 provides explicit guidance on when to use this tool versus the alternative: 'For raw API access, use gorgias_retrieve_reporting_statistic.' It also gives actionable conditions for problematic queries (e.g., use granularity: "none" for many rows) and warns about broken scopes that return API errors. This is strong, practical usage guidance.

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