get_read_receipts

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, covering safety and scope. The description adds minimal behavioral context by specifying it queries date_read and date_delivered columns, but doesn't disclose details like response format, pagination, or rate limits. With annotations providing core safety info, this earns a baseline score for adding some value without contradiction.

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 concise and front-loaded, with the first sentence stating the core purpose and the second providing technical details. Both sentences earn their place by clarifying scope and data sources. Minor improvement could come from integrating the two sentences more smoothly, but it's efficiently structured.

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 (analytics query with 4 parameters), rich annotations, and 100% schema coverage, the description is adequate but lacks output details (no output schema provided) and usage context. It covers the what but not the how or when, leaving gaps in completeness for an analytics tool.

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%, with all parameters well-documented in the input schema. The description adds no parameter-specific semantics beyond implying date-range filtering through 'Queries date_read and date_delivered columns', which is already covered by the schema's date_from/date_to fields. This meets the baseline for high schema coverage without additional value.

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 with specific verbs ('queries') and resources ('read receipt and delivery timing analytics'), distinguishing it from sibling tools like 'message_stats' or 'contact_stats' by focusing on read/delivery timing metrics rather than general statistics. It explicitly mentions the data columns involved ('date_read and date_delivered columns'), making the scope 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 provides no guidance on when to use this tool versus alternatives. While it mentions querying specific columns, it doesn't indicate scenarios where this tool is preferred over sibling tools like 'message_stats' or 'contact_stats', nor does it mention prerequisites or exclusions. The agent must infer usage from the purpose alone.

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