Generate a tracked affiliate link for a product. Requires the product UUID (returned by list_products / find_products). Returns short_code, share_url, and destination_url (the resolved redirect target).
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes | Product UUID (required) | |
| campaign_id | No | Optional campaign UUID to associate the link with (attribution) | |
| product_short_code | No | Legacy alias for product_id — UUID only |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnlyHint=false, destructiveHint=false, and idempotentHint=false. The description adds behavior beyond those flags by saying the call generates a link and that destination_url is the resolved redirect target, which clarifies what the generated short_code/share_url will point to.
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 sentences front-load the purpose, give the prerequisite, and list the return values without repetition or filler. Every clause adds useful information for selecting and invoking the tool.
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?
There is no output schema, so the description correctly carries the burden of indicating what will come back: short_code, share_url, and destination_url. Combined with the prerequisite, this is enough to for an agent to call the tool 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?
The schema already describes all three parameters (100% coverage), so the baseline is 3. The description additionally helps the agent choose the correct parameter value by saying the product UUID is provided by list_products/find_products, which is useful source information.
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 opens with a concrete verb and resource: 'Generate a tracked affiliate link for a product.' It also states the required input source ('product UUID returned by list_products / find_products') and what the call returns, making its purpose easy to distinguish from campaign, profile, and content tools among the siblings.
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 a clear workflow prerequisite: obtain the product UUID from list_products/find_products before calling this tool. It does not explicitly list alternatives or when not to use it, but the context is clear enough for the intended generation flow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools clearly target distinct resources and actions, but there is some overlap: get_profile and get_my_earnings both expose balance/cap information, and list_my_profiles could be confused with get_profile. The descriptions are generally clear enough to avoid serious misselection.
Every tool name follows a consistent snake_case verb_noun pattern: get_product, list_campaigns, submit_post, update_profile, etc. The verbs match the intended actions, and there are no mixed naming conventions or vague style deviations.
Twenty tools is slightly heavy, but the count is reasonable for the scope: the server covers products, campaigns, posts, earnings, profiles, notifications, asset uploads, and AI tool usage/reviews. Each tool serves a recognizable purpose, so the size feels like breadth rather than redundancy.
Core workflows are present—search products, get campaigns, apply, generate tracking links, submit posts, view earnings, manage notifications—but there are notable gaps. There is no way to list past posts or retrieve a post_id except from submit_post, no list of campaign applications, and no tool discovery endpoint for the AI tool slugs used by declare_tool_usage and write_tool_review.
