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

The description discloses substantial behavior beyond the annotations: geo_ids expand through the containment hierarchy, the response echoes the EXPANDED query with query_id, corroboration_policy strictly rejects unknown fields, and tenant_id is a namespacing sub-label restricted to the caller's own account. These are non-obvious behavioral details an agent needs to predict results correctly.

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 dense but every sentence carries operational value: purpose, when-to-use, expansion behavior, response shape, validation strictness, event delivery, and tenant scoping. It is front-loaded with the core purpose and then layers constraints in a logical order without 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?

The description is strong overall: it covers return behavior via query_id, how matching events are delivered, and how to address the query later. The only completeness gap is that two optional parameters, lang_scope and min_severity, are left undocumented despite zero schema descriptions and no output schema to clarify their role.

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?

With 0% schema description coverage, the description compensates well by explaining geo_ids expansion, accepted disruption_types, expires_at format, exact corroboration_policy values, and tenant_id semantics. However, lang_scope and min_severity are not explained at all, leaving two optional parameters to be inferred from their names 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: register a standing disruption query for continuous real-time monitoring of geo_ids and disruption_types. It clearly distinguishes this from historical sentiment tools by saying it is for ALERTING on future disruptions, not historical sentiment, and lists the exact accepted disruption types.

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?

It explicitly states when to use the tool: when an agent needs alerting on future disruptions, not historical sentiment. It also explains how the registered query connects to list_disruption_events and registered webhooks, and how tenant_id ties it to list_standing_queries and delete_standing_query, giving clear operational routing.

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