wafle_ai_product_describe

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

With no annotations provided, the description carries the full burden and discloses key behavioral traits: it reads product data, runs an LLM, creates a pending review job rather than directly modifying the product, and requires an accept step to apply changes. Also notes approximate length and tone options, providing clear expectations.

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 short paragraphs front-load the purpose and workflow, then provide parameter specifics. Every sentence contributes useful information without redundancy or fluff.

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 explains the end-to-end behavior and side effects, but does not explicitly describe the return value (e.g., job ID or status), which would be helpful given the absence of an output schema. Still, the workflow is clear enough for an agent to use correctly.

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 covers sku, slug, and locale explicitly. The description adds meaning for the undocumented parameters ton and length_words: tone is listed as 'persuasivo' | 'tecnico' | 'breve', and length is described as approximate words (±15%), complementing the schema's defaults and constraints.

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 'Generate a sales copy description for a product' and outlines the full workflow: reads catalog data, runs the configured LLM, and stores output as a pending review job. This distinguishes it from sibling tools like wafle_ai_categorize and wafle_ai_translate.

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 clear context for when to use this tool (generating sales copy) and explains the follow-up action (call wafle_ai_jobs_accept to apply). It does not explicitly mention alternative tools or exclusions, but the purpose is specific enough to avoid confusion.

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