numeral_list_transaction_refundsList all refunds recorded against a transaction. Returns {refunds:[...]}. Numeral: GET /tax/transactions/{transaction_id}/refunds.
| Name | Required | Description | Default |
|---|---|---|---|
| transaction_id | Yes | The Numeral transaction id (tr_...). |
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 description adds context beyond the readOnlyHint annotation by specifying the return format and the underlying API endpoint. It discloses the behavior (listing) and output structure, which is helpful for an agent.
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?
The description is concise, containing one sentence and a code snippet with endpoint and return type. It front-loads the purpose and provides essential details without unnecessary verbosity.
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?
Given the tool's simplicity (one required parameter, no output schema), the description is fairly complete: it explains the function, return format, and API endpoint. It does not cover pagination or ordering, but these are not critical for a basic list tool.
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% with a clear description for transaction_id. The description does not add additional meaning to the parameter beyond what is in the schema, so a baseline score of 3 is appropriate.
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 'List' and resource 'refunds recorded against a transaction', clearly distinguishing it from siblings like 'numeral_create_refund' (creates refunds) and 'numeral_get_transaction' (gets transaction details). It also specifies the return format.
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 context (listing refunds for a transaction) but does not explicitly state when to use this tool over alternatives or mention exclusions. No when-not-to-use guidance is provided.
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.
Each tool has a distinct purpose with no overlap. Tax calculations, product/customer management, transaction recording, refunds, and health check are clearly separated.
All tools use a consistent 'numeral_verb_noun' pattern with snake_case. Verbs are standard (calculate, create, get, list, ping) and maintain predictability.
11 tools cover the core functionalities of tax calculation, product/customer management, transaction recording, and refunds without unnecessary extras.
Core CRUD is incomplete: missing lists for customers and transactions, and no update/delete endpoints. While key workflows are covered, significant operational gaps exist.