create_anomaly_tickets

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

Lacking annotations, the description states it uses the first configured ticketing provider and only processes anomalies without tickets. It does not disclose failure behavior if no provider is configured, rate limits, or whether ticket creation is idempotent. This is acceptable for a simple tool but not fully transparent.

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 short, front-loaded with the action, and includes structured args and examples. It is efficient but could further condense the examples into a single line.

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 one-parameter tool, the description covers purpose and input adequately but omits return value or success/failure indicators. Since there is no output schema, the description should ideally state what the tool returns (e.g., list of created tickets). This gap reduces completeness.

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 schema has 0% description coverage, but the description fully documents the 'limit' parameter with its default and purpose. This adds necessary meaning beyond the schema's bare type definition.

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 it creates tickets specifically for active high/medium anomalies without existing tickets, and lists supported ticketing providers (Jira, Linear, GitHub Issues). This distinct purpose differentiates it from sibling tools like create_rightsizing_tickets or create_ticket.

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 defines the scope (anomalies that are active, high/medium severity, and ticketless) and the first-configured provider behavior, guiding when to use this tool. However, it does not contrast with alternatives like create_ticket or create_kubernetes_waste_tickets.

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