jobber_list_work_requestsList work requests raised with a provider through Jobber Client Hub, including current section and metadata for each request.
Work requests you have raised with a provider through their Jobber Client Hub, with their current section (state) and metadata rows. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| hub | No | Which provider hub to read, by label. Omit when only one is configured. |
Changes observed during successful MCP inspections.
v0.4.0Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"v0.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is covered. The description adds useful behavioral context beyond that: it scopes results to requests the user raised via a provider hub and indicates that each result includes its current section/state and metadata rows. This adds meaning without contradicting annotations.
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 one dense, front-loaded sentence plus a 'Read-only' tag. There is no filler or repetition beyond the annotation-backed read-only note, and every phrase adds scope or content detail.
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 tool with one optional parameter, no output schema, and strong annotations, the description adequately explains which records are returned and what fields they carry. It could mention ordering or pagination, but given the low complexity this is nearly complete.
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 parameter 'hub' is already fully documented in the schema with 100% description coverage, so the description does not need to compensate. It reinforces the Client Hub context, but it adds no parameter-level detail beyond what the schema provides; baseline 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 names a specific verb ('list'), a specific resource ('work requests'), and the exact scope ('you have raised with a provider through their Jobber Client Hub'). It also previews the returned content ('current section (state) and metadata rows'), making it easy to distinguish from sibling list tools such as jobber_list_appointments and jobber_list_invoices.
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 establishes clear context: this tool is for work requests raised by the caller through a provider's Client Hub, not for other Jobber record types. It does not explicitly name alternatives or say when not to use it, but the resource and scope make the correct choice obvious among the sibling list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.