data_list_clientsGet the list of clients registered in the shop, including contact info, loyalty points.
| 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?
Annotations already declare readOnlyHint=true, so the description's statement 'Get the list' is consistent. The description adds behavioral context by noting what data is included (contact info, loyalty points), which is 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?
The description is a single, front-loaded sentence that immediately conveys the purpose. No redundant or unnecessary words.
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 tool with one optional parameter, no output schema, and annotations covering safety, the description adequately explains the tool's output and usage. Complete and sufficient.
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 the 'format' parameter fully described via enum and default. The description does not add additional parameter semantics beyond the schema, so baseline 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 clearly states the verb 'Get' and the resource 'list of clients', and specifies included fields (contact info, loyalty points). It distinguishes from sibling tools like client_add, client_edit, and other data_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?
The description implies the tool is for retrieving client lists but does not explicitly state when to use it over alternatives or provide exclusions. The context of sibling list tools suggests it's the appropriate tool for clients, but no direct guidance is given.
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.