Get a credit note
get_credit_noteFetch a single credit note by id. Quaderno API: GET /credit_notes/{id}.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The resource id. |
get_credit_noteFetch a single credit note by id. Quaderno API: GET /credit_notes/{id}.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The resource id. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare `readOnlyHint: true`, so the safe read behavior is covered. The description adds the HTTP GET endpoint but no additional behavioral context such as error cases or response format. It is consistent with annotations and does not contradict them.
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, front-loaded sentences with no filler. The first sentence states the operation; the second provides the exact API endpoint. Every word earns its place.
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 one-parameter read operation, the combination of description, schema, and annotations is complete. The agent knows the resource, the lookup key, and the read-only nature. No output schema exists, but the return value is implied by the resource name and a simple GET operation.
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%: the `id` parameter already has a description ('The resource id.'). The tool description only repeats 'by id' and adds no new meaning, so the schema carries the parameter semantics.
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 ('Fetch'), a specific resource ('a single credit note'), and the lookup criterion ('by id'). This clearly distinguishes it from `list_credit_notes` and the other `get_*` siblings, so an agent can identify what this tool does without opening schemas.
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 implies usage when the agent has a specific credit note id and needs one record. However, it does not explicitly contrast with `list_credit_notes` or mention when not to use it, so it stops short of a 5.
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 target distinct resources and actions, but create_invoice and create_transaction both generate tax-compliant sale documents, making their boundary unclear. calculate_tax also overlaps conceptually with the tax calculation embedded in create_transaction, though the descriptions help separate the read-only case.
The set follows a consistent verb_noun pattern across get_, list_, create_, and update_ tools, with clear singular/plural usage. calculate_tax and ping fit the style, but quaderno_request is a generic escape hatch that breaks the predictable naming convention.
At 23 tools, the server is on the heavy side and falls in the 16-25 range that feels less scoped than ideal. However, the count is somewhat justified by the many distinct entity types covered, including contacts, invoices, items, credit notes, expenses, receipts, jurisdictions, and webhooks.
Core workflows like calculating tax, creating invoices/transactions, and managing contacts/items are covered, and every exposed resource has get/list access. Missing update/delete operations for most resources, read-only webhooks, and no direct creation paths for expenses/receipts/credit notes leave notable lifecycle gaps.