Retrieve detailed contact and partner records, including addresses, bank accounts, credit limits, discounts, and maturity terms, to support accounting decisions.
Query the address book (contacts/partners) with full detail: addresses, bank accounts, credit limits, discount, maturity terms
| 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?
There are no annotations, so the description carries the behavioral disclosure burden. It does state this is a read/query operation and lists what data categories are included. However, it does not mention response shape, pagination behavior, or how the GraphQL order/where clauses affect results.
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 sentence that front-loads the verb and resource and then compacts the detail scope into a short list. Every phrase contributes meaningful information with no repetition 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 simple read tool with no required parameters and fully documented schema parameters, the description provides the essential context: what is queried and what level of detail is returned. The lack of an output schema leaves return format unspecified, but the listed data categories give sufficient expectation for an agent.
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 input schema has 100% description coverage for all four parameters (skip, take, order, where), so the schema already explains them. The description adds no extra parameter-level detail, which is acceptable given the full schema coverage.
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 uses a specific verb ('Query') and resource ('address book (contacts/partners)') and enumerates the fields returned, making the tool's scope unmistakable. It also distinguishes itself from sibling create/delete address tools by clearly positioning itself as a read operation.
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 clearly signals that this tool is for querying address book data with full detail. It does not explicitly state when-not-to-use it, but the presence of m3_create_address and m3_delete_address among siblings makes the intended usage boundary inferable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.