Get Gong Call Statistics

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds behavioral context by specifying the exact return content in the 'Returns' line: total calls, average duration, direction breakdown, and top participants. This goes beyond the annotations and helps the agent understand what the call actually provides.

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 well-structured: one clear main sentence, a use-case sentence, an Args list, a Returns line, and an example. It is not excessively verbose and front-loads the core purpose. The example is useful but could be trimmed; overall, it earns its keep.

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?

The tool has no output schema, so the description bears the burden of explaining return values, which it does in the 'Returns' line. It also covers parameters and a practical example. Missing details like timezone handling or date-inclusivity are minor for an aggregate stats tool. The description is sufficiently complete given the tool's simplicity.

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 has 100% coverage with descriptions for all three parameters. The description repeats the parameter semantics in an 'Args' section without adding meaningful new information beyond what the schema provides. Since schema coverage is high, a baseline of 3 is appropriate.

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 function: 'Get aggregate call statistics for a date range' with specific metrics (total calls, average duration, call breakdown). This distinguishes it from siblings like gong_search_calls and gong_get_transcript, which focus on individual calls or transcripts.

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 a clear use case: 'Useful for pipeline reviews and rep activity analysis.' It implies this is for aggregate data rather than individual-call queries, but it does not explicitly exclude alternatives or name when not to use it.

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