list_ai_actions

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds useful context about filtering behavior and the caution against automatic filtering, but doesn't provide additional behavioral details like pagination, rate limits, or what constitutes an 'AI Action' beyond the parenthetical '(Prompts)'. No contradiction with annotations exists.

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 appropriately sized at three sentences, with the core purpose stated first. The second sentence explains optional filtering, and the third provides important usage guidance. No wasted words, though the structure could be slightly improved by combining the filtering explanation into one smoother sentence.

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?

Given the tool's moderate complexity (2 optional parameters, no output schema), the description covers the basics adequately but has gaps. It explains what the tool does and provides filtering guidance, but doesn't describe the return format, pagination, or how results are ordered. With annotations covering safety, this is minimally complete but could benefit from more behavioral context.

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 carries the full burden of explaining parameters. It successfully explains both parameters: 'owner_type' (with enum values) and 'workspace_id' (implied by 'filter by workspace id'). The description adds meaningful context about when to use these filters, though it doesn't specify format requirements for workspace_id.

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 the verb 'List' and resource 'AI Actions (Prompts)', making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_ai_action_responses' or 'run_ai_action', which could cause confusion about when to use each. The parenthetical '(Prompts)' adds useful clarification about what AI Actions are.

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 provides explicit guidance on when to use the optional filters ('Do not use unless the user explicitly requests it'), which is helpful for agent decision-making. However, it doesn't explain when to use this tool versus similar sibling tools like 'get_ai_action_responses' or 'run_ai_action', leaving some ambiguity about tool selection in context.

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