Queue AI optimization for product fields by submitting a product UUID. Specify fields like title or meta description to improve SEO content.
POST /api/v1/products/{id}/optimization — queue AI optimization for one or more product fields (queued, 202). EXPENSIVE: 10 req/min limit.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Product UUID | |
| fields | No | Fields to optimize. Omit to optimize all default fields. |
Changes observed during successful MCP inspections.
v0.0.3Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate non-idempotent and non-destructive. The description adds 'queued, 202' (asynchronous) and the 10 req/min limit, which are behavioral details beyond annotations. It does not contradict annotations. No further behavioral caveats are needed beyond these.
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 a single sentence that packs endpoint, action, async behavior, and rate limit. It is front-loaded and every element earns its place. No redundancy or 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?
For a tool with two simple parameters and no output schema, the description covers the essential aspects: what it does, the asynchronous nature, and the rate limit. It could mention how to track the queued job (e.g., via beaconed_optimizations_list), but the sibling tools are not referenced. Still, the description is adequate for an agent to call it 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 coverage is 100% and the description adds meaning to the 'fields' parameter by explaining 'Omit to optimize all default fields.' It also ties the 'id' to a product. This adds value beyond the bare schema, which already describes the fields enum.
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 states a clear action ('queue AI optimization'), the resource ('products/{id}/optimization'), and scope ('one or more product fields'). It implicitly differentiates from bulk optimization (sibling beaconed_bulk_optimize) by focusing on a single product ID, and from score-related tools by specifying an optimization action.
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 gives context (queued, 202, rate limit) but does not explicitly state when to use this versus alternatives. It does not mention 'use beaconed_bulk_optimize for multiple products' or exclude other cases. The rate limit warning implies careful use, but no explicit when-to-use or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.