data_list_vatsRetrieve the list of VAT rates configured in the shop, including their title, rate percentage, and optional accounting chapter.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Response format: 'json' (default), 'csv', or 'html' | json |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description confirms read-only behavior, which matches the readOnlyHint annotation. However, no additional behavioral traits (e.g., pagination, default ordering, response size limits) are disclosed beyond the annotation.
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, well-structured sentence that immediately conveys the tool's purpose and key returned fields. No extraneous 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 simple list retrieval with one optional parameter, the description adequately covers the return fields and the tool's core action. Lack of output schema is acceptable given the straightforward nature.
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 single optional parameter 'format' is fully documented in the input schema with enum values and default. The description adds no new meaning about the parameter, so baseline score applies.
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 clearly states it retrieves a list of VAT rates and specifies the fields included. It distinguishes itself from sibling list tools by naming 'VAT rates', but does not explicitly differentiate from similar list tools.
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?
No guidance on when to use this tool versus alternatives or any prerequisites. The description lacks context about filtering, sorting, or typical use cases.
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 targets a distinct entity or action (account, client, order, product, payment, VAT, etc.), with clear naming like 'account_create' vs 'account_edit' and 'data_list_' prefixed listings. No overlapping purposes detected.
All tool names use snake_case and follow a consistent verb_noun pattern (e.g., account_create, client_add, data_list_clients). Even compound names like auth_login_with_otp adhere to this structure.
41 tools is high but justified by the wide scope of a POS/accounting system (accounts, clients, orders, products, payments, VAT, reports). Slightly above the typical range but well-scoped.
The tool surface covers CRUD for all major entities (clients, departments, products, VAT, payment modes, orders), plus queries, reports, and authentication. No obvious gaps for a small business management server.