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

Beyond annotations, the description discloses important behavioral traits: it 'does not infer consensus,' it records accepted contributions and remaining disagreement, and a successful user-approved resolution becomes active guidance returned by get_induction. It also warns that AI votes alone cannot activate guidance, which is non-obvious and valuable context.

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 long, front-loads the core action, and every sentence adds a distinct piece of information: what the tool does, what it does not infer, and what downstream effect a successful resolution has. There is no filler or repetition.

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 7-parameter tool with no output schema, the description provides the essential behavioral context: the requirement for user_approved=true, the distinction from consensus, and the side effect on get_induction. It leaves some details implicit, such as what happens when user_approved=false and the exact use of idempotency_key, but the annotations cover idempotence and the core decision criteria are clear.

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?

There are no parameter descriptions in the input schema (0% schema coverage), so the description must compensate. It does add meaning for user_approved, accepted_contribution_ids, and unresolved_points by matching 'requires user_approved=true' and 'records accepted contributions and remaining disagreement.' However, other parameters like idempotency_key, rationale, and resolution are not given semantic clarification in the description.

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: 'Close a deliberation with the user's explicit decision.' It also clarifies the precise nature of the operation by stating it records accepted contributions and remaining disagreement rather than inferring consensus, and it distinguishes its effect from AI voting authority, which clearly separates it from sibling deliberation 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?

The description gives clear context for when to use this tool: after the user has made an explicit decision and when user_approved=true. It also states a key when-not condition: AI votes alone have no activation authority. It does not explicitly name alternative tools to use instead, but the conditions are concrete enough for an agent to route correctly.

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