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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the agent knows it's a safe read. The description adds substantial behavioral context beyond annotations: it returns only content-free aggregates, lists explicit categories of data it NEVER returns (query text, answers, feedback bodies, etc.), and clarifies edge-case semantics (open + done need not equal ticket total due to cancelled tickets). This is rich, non-redundant disclosure.

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?

Every sentence in the description adds value: the front-loaded 'OPERATOR ONLY' flags access restrictions, the scoping/differentiation sentence is functional, the aggregate list is comprehensive but compact, and the exclusions and caveat are critical. The description is appropriately sized for the tool's complexity—there is no fluff.

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 has 0 params and an output schema exists, the description goes above and beyond by itemizing the aggregate metrics, specifying the never-returned data types, and clarifying the relationship between counts. It also covers permission errors, making it complete for an agent to safely invoke. The output schema enriches the return structure, but the description independently ensures full contextual understanding.

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 tool has 0 parameters, so the input schema provides no parameter semantics. Per rubric, 0 params = baseline 4. The description does not need to explain parameters, but it compensates by thoroughly describing the output dimensions (account counts, sessions, tickets, pipeline, etc.), which effectively defines what the tool returns. No additional parameter explanation is possible.

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 a specific verb+resource: 'cross-owner analytics for the META COUNCIL PLATFORM itself'. It immediately distinguishes from the sibling get_workspace_metrics by explicitly stating what it is NOT ('the caller's workspace') and pointing to the alternative. The scope is 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?

Provides explicit when-to-use and when-not-to-use guidance: use for cross-owner platform analytics, not for caller workspace (directing to get_workspace_metrics). It also states the exact permission prerequisites ('platform:admin scope AND an ADMIN_EMAILS operator account') and the consequence for others ('permission error'). This is model usage guidance.

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