orb_list_plansList plans configured in the Orb account. Orb API: GET /plans.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max items to return (1–100, default 20). | |
| cursor | No | Opaque pagination cursor (from pagination_metadata.next_cursor). | |
| status | No | Filter by plan status. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds the endpoint and account scoping but does not disclose pagination behavior, default status behavior, or response shape. No contradiction with annotations exists.
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 sentences convey the operation, scope, and API endpoint without filler. Every word contributes useful information, and the description is appropriately front-loaded.
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 optional-parameter read-only list operation with fully documented parameters, this is nearly complete. It could be improved by stating the response shape or pagination behavior, but the cursor parameter and endpoint make it sufficiently usable.
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?
All three parameters (limit, cursor, status) are fully described in the input schema, so the schema carries the semantic burden. The description adds no additional parameter-level detail, which is acceptable here due to 100% schema coverage.
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 names the specific operation (List) and resource (plans), scopes it to the Orb account, and provides the exact endpoint. This clearly distinguishes it from orb_get_plan (single-plan lookup) and other orb_list_* siblings.
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 when to use this tool by saying 'List plans configured in the Orb account,' but it does not explicitly state when to prefer this over orb_get_plan or mention any alternatives/exclusions. Usage is inferable but not directly guided.
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.