get_analytics_group_models

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds important behavioral context: 'Enterprise-gated. Returns 403 on non-Enterprise Portkey plans.' This discloses access restrictions and error outcomes. It also mentions pagination, which is not in annotations.

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 three sentences, each serving a distinct purpose: what the tool does, when to use it vs alternatives, and enterprise restriction. No wasted words.

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 complexity (31 params, 2 required, nested objects) and presence of an output schema, the description adequately covers return fields and pagination. It also mentions the enterprise gating, which is critical for usage. The description is sufficient for an agent to understand the tool's behavior.

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 all 31 parameters have descriptions in the input schema. The description does not add parameter-specific meaning beyond summarizing the high-level purpose. Baseline score 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 verb 'Get' and the resource 'paginated per-model breakdown'. It specifies the returned fields (total_groups, group_count, models array with request count, cost, token usage). It also distinguishes from siblings get_token_analytics and get_cost_analytics by mentioning their alternative use case.

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 says when to use this tool ('compare model cost, popularity, and efficiency') and when not to ('use get_token_analytics or get_cost_analytics for time-series trends instead'). It names specific alternative tools, providing clear guidance.

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