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

With no annotations provided, the description carries the full burden of behavioral disclosure—and it delivers. It clearly reveals the approval-required nature: returns `{ status: 'approval_required', approval_url, polling_url, expires_in }`, instructs to print the URL and poll, and specifies the approval gate (target agent's owner must match `Agent.ownerUserId`). This goes far beyond a simple call-to-action and sets correct expectations for an interactive, human-in-the-loop flow.

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 a single dense paragraph, but every sentence contributes value: purpose, contrast, return format, polling instructions, approval gate, and use cases. It is not as scannable as bullet points, but it avoids fluff and front-loads the primary purpose. Slightly longer than necessary, yet all content is relevant and actionable.

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 (approval flow, polling, multiple return fields) and the absence of an output schema, the description fully compensates. It specifies the exact response shape, how to act on it (print URL, poll), the approval constraint, and the reason for escalation. An agent has enough context to invoke the tool and handle the result correctly without additional information.

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 both parameters with descriptions, so the baseline is 3. The description adds meaningful guidance beyond the schema: it tells how to obtain `target_agent_id` ("Get from list_workspace_members or list_workspaces") and reinforces the purpose of `reason` ("surface a useful `reason` so the human knows why"). This elevates the parameter usability beyond the schema alone.

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 opens with a specific verb and resource: "Ask the human owner to revoke ANOTHER agent's active API key (sibling agent)." It explicitly contrasts with the self-only `revoke_api_key` tool, making the tool's unique purpose unmistakable. This clearly distinguishes it from siblings like `revoke_api_key` and `request_rotate_agent_key`.

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 states when to use this tool: "The MCP `revoke_api_key` tool is self-only by design; this is the cross-agent escalation path." It further lists concrete trigger scenarios: "credential leakage, misbehaviour, or a stuck sibling that needs a clean kill." This gives an agent clear decision criteria for selecting this tool over alternatives.

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