get_load_balancer_list

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

No annotations provided, so description carries full burden. Describes pagination (limit/offset), include_all option, and what information is displayed (VIP, status, listeners, provisioning status). Does not mention authentication or side effects, but as a read-only list, this is sufficient.

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?

Well-organized with clear sections: functions, use cases, args, returns. Every sentence adds value; no fluff. Front-loaded with purpose.

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?

Has output schema, so detailed return structure is covered elsewhere. Description notes returns 'JSON string containing load balancer details with summary statistics', which suffices. Complete for a list tool.

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 coverage is 0% (only defaults and types). Description's 'Args' section explains each parameter: limit (1-200, default 50), offset (default 0), include_all (default False). Adds context missing from schema.

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?

Description specifies 'Retrieve comprehensive list of OpenStack load balancers with detailed information' and lists functions like listing all LBs, showing VIP/status/listeners. This clearly distinguishes it from sibling tools like get_load_balancer_details (single LB) or get_load_balancer_listeners (listeners only).

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?

Provides explicit use cases with example user requests ('Show me all load balancers'). Lacks explicit when-not-to-use or alternatives, but the context is clear enough for an AI to decide.

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