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

With no annotations, the description carries the full burden and does well: it discloses the auth constraint (human session only, not API key/assistant), the state gate (awaiting_approval), that eligibility is re-validated, and the side effect (the call is queued). It stops short of describing what queued means operationally or whether the action is reversible.

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?

One dense sentence with the most important constraint (human session only) front-loaded in the parenthetical, followed by the state precondition and the resulting effect. No filler, though the parenthetical slightly interrupts the flow of the primary action.

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?

For a 2-parameter mutation with no annotations and no output schema, the description supplies the auth model, the state precondition, the re-validation behavior, and the outcome. What it lacks is parameter-level clarification and any statement of the response, but the core invocation requirements are covered.

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 0% for both id and workspaceId, so the schema provides no meaning, and the description does not compensate. It refers to 'a call' and an implicit workspace context but never explains which parameter is the call identifier versus the workspace scope, or the UUID format expectations.

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?

States a specific verb (approve), a specific resource (a call an AI assistant asked for), and the exact precondition state (status awaiting_approval). An agent can distinguish this from calls_decline, calls_cancel, and calls_create without inspecting other tools.

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?

Gives clear preconditions for use: the caller must be a signed-in person (not an API key or assistant) and the call must be in awaiting_approval status. It does not explicitly name the alternative (calls_decline) or restate the condition that would route an agent there, which is the only gap.

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