list_productsRetrieve products with their variants and SKUs, and filter by full-text search, status, collection, or category.
Lists products with their variants (SKUs). Filter by full-text, status, collection or category.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | ||
| limit | No | Number of records (max 200) | |
| offset | No | Records to skip (pagination) | |
| status | No | ||
| category_id | No | ||
| collection_id | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds that results include variants (SKUs), which is useful return-shape context, but says nothing about pagination behavior, default result counts, or ordering.
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 sentences, zero filler, with the core action front-loaded before the filter list. Every clause carries information.
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 read-only list tool with no output schema, the definition covers scope and available filters adequately. It omits pagination/default-limit behavior that an agent might need, but the schema supplies limit and offset documentation.
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 description coverage is only 33% (limit and offset), yet the description maps meaningful filter semantics: full-text via q, and filtering by status, collection, and category. That covers four of the six params conceptually, compensating well for the sparse schema.
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?
States a specific verb and resource ('Lists products with their variants (SKUs)') and even clarifies return granularity (variants/SKUs). It does not explicitly name sibling tools like get_product, but the singular/plural split makes the distinction obvious to an agent.
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 implies usage by naming the available filters, but never states when to prefer this over get_product or update_product, nor any prerequisites. Usage is inferable rather than guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.