orb_list_customersList customers in the Orb account. Orb API: GET /customers.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max items to return (1–100, default 20). | |
| cursor | No | Opaque pagination cursor (from pagination_metadata.next_cursor). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description does not need to restate read-only safety. It adds the API endpoint and account scope, but does not disclose additional behaviors such as response shape or pagination behavior beyond what the parameter schema already indicates.
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 two short, purposeful sentences with no filler. The main action and scope are front-loaded, and the API endpoint is useful additional context.
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-only listing tool with fully documented parameters and no output schema, the description is nearly sufficient. It clearly identifies what is returned at a high level, though it could explicitly mention the paginated list envelope for extra clarity.
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 covers both parameters completely, including min/max and default for limit and the meaning of cursor. The description adds no parameter-specific meaning, which is acceptable given the high schema coverage; baseline 3 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 uses an explicit verb-resource pair, 'List customers', and scopes it to the Orb account. It also cites the underlying API endpoint, making the intent unambiguous and distinguishable from sibling tools like orb_get_customer or orb_list_subscriptions.
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 primary usage is clear: call this tool when you need to list customers. However, the description does not explicitly compare it with alternatives such as orb_get_customer or clarify when not to use it, leaving the guidance largely implied by the name and sibling set.
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.
Every tool name clearly specifies a distinct action and resource (e.g., list_subscriptions vs get_subscription). There is no ambiguity between tools as each targets a unique combination of verb and noun.
All tool names follow a consistent pattern: 'orb_<verb>_<resource>' in snake_case. This makes them predictable and easy to distinguish.
With 26 tools, the set covers many resources and operations for a billing platform. While slightly above typical range, each tool justifies its existence given the domain complexity.
The tool surface provides extensive read capabilities and basic customer CRUD, but lacks create/update/delete for most other resources (e.g., subscriptions, invoices) and missing operations like void or cancel. This creates notable gaps for full lifecycle management.