generate_content_with_ai

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

With no annotations provided, the description carries full disclosure burden. It successfully explains the conversational state management (multi-turn via ai_id), but omits safety-critical details such as rate limits, whether generation is billable, or if content is automatically persisted versus just returned.

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?

Two efficiently constructed sentences. The first front-loads the core purpose, while the second adds the essential multi-turn context. Zero duplication of schema details or redundant filler.

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 schema's rich parameter documentation (100% coverage) and the tool's moderate complexity, the description covers the essential behavioral context (AI generation, conversation continuity). It effectively compensates for the missing output schema by implying the conversational cycle through parameter descriptions, though it could explicitly mention that the response contains new ai_id/chat_progress values for subsequent calls.

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?

While the schema has 100% description coverage (baseline 3), the description adds valuable semantic context by framing ai_id and chat_progress within the 'multi-turn conversation' workflow, helping the agent understand these parameters form a conversation state protocol.

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 specific action (Generate), resource (social media content text), and mechanism (using RecurPost AI). It distinguishes from the sibling 'generate_image_with_ai' by explicitly specifying 'text' content.

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 implicit usage guidance by explaining that ai_id enables 'multi-turn conversations,' indicating when to populate that parameter. However, it lacks explicit guidance on when to use this tool versus siblings like 'generate_image_with_ai' or prerequisites like authentication.

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