Retrieve comprehensive stock card data: pricing, stock levels, barcodes, weight, warranty, and categories. Apply filters and pagination to find specific inventory records.
Query stock/inventory cards with full detail: pricing, stock levels, barcodes, weight, warranty, categories
| Name | Required | Description | Default |
|---|---|---|---|
| skip | No | Records to skip | |
| take | No | Number of records | |
| order | No | GraphQL order clause | |
| where | No | GraphQL where filter |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full disclosure burden. It does disclose the scope of returned data (the field list), which is genuine behavioral information. However, it omits significant traits: results are paginated via skip/take with a 100-record cap, and the where/order parameters require GraphQL syntax knowledge. Partial disclosure only.
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?
A single front-loaded sentence with zero filler; 'Query stock/inventory cards' leads and the field enumeration earns its place by telling the agent what detail to expect. It is appropriately sized, though a second sentence with usage routing would have improved it without bloat.
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?
With no output schema, the field list in the description serves as the only return-value information, which is helpful. But for a tool with four parameters, no annotations, and a large sibling set, the missing usage guidance and behavioral details (pagination cap, GraphQL syntax requirements) leave the agent only partially informed.
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 100%, so the schema already documents all four parameters (skip, take, order, where), placing the baseline at 3. The description adds no parameter-level meaning beyond the schema — it never explains the GraphQL filter/order clauses or pagination behavior, which would have genuinely helped.
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 specific verb ('Query') and resource ('stock/inventory cards') and enumerates the exact detail fields returned (pricing, stock levels, barcodes, weight, warranty, categories). The read verb clearly separates it from the m3_create_stock_card and m3_delete_stock_card siblings, though it does not explicitly differentiate it from the similarly named read tool m3_stock_lists.
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?
There is no guidance on when to use this tool versus the many overlapping stock-related siblings (m3_stock_lists, m3_stock_documents). No conditions, exclusions, or alternative tool names are provided, and with 60+ sibling tools the agent must infer usage purely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.