check_service_area
Use when the user provides a London postcode or asks whether TaskMan covers their area.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| postcode | Yes | ||
| service_type | No |
Use when the user provides a London postcode or asks whether TaskMan covers their area.
| Name | Required | Description | Default |
|---|---|---|---|
| postcode | Yes | ||
| service_type | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, but it only says 'covers their area' without disclosing behavior such as whether it's a read-only lookup, how service_type affects results, or what response format to expect. This is a significant transparency gap for a tool with no annotation support.
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, front-loaded sentence that clearly communicates the tool's purpose and use case. Every word earns its place, and there is no redundant 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 check tool with one required parameter, the description is adequate but incomplete. It covers the primary use case but omits details about the optional service_type parameter and the return value, which are relevant for a complete understanding. The lack of annotations and output schema makes this a notable gap.
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 0%, so the description must compensate, but it only implicitly mentions the postcode parameter in the usage context. The optional service_type parameter with its enum values is not explained at all, leaving the agent without guidance on how to use it or whether it modifies coverage results.
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 tool checks if TaskMan covers a London postcode, using a specific verb and resource. It distinguishes from siblings like check_availability by focusing on area coverage rather than service availability.
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 explicitly provides when-to-use scenarios: when the user provides a London postcode or asks about coverage. It does not mention when not to use or alternatives, but the context is clear enough for an agent to select this tool appropriately.
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.
Some tools overlap in purpose, such as check_availability vs get_customer_availability and the various verification entry points. Descriptions clarify the context of each, but an agent could still misselect without careful reading.
All tools follow a consistent verb_noun pattern with snake_case, e.g., check_availability, create_booking_request, get_booking_status. This makes the naming predictable and easy to navigate.
With 20 tools, the server is on the heavier side but the scope is broad, covering booking, customer verification, payments, and provider matching. The count feels slightly high but each tool serves a distinct step in the workflow.
The tool surface covers the full booking lifecycle from availability and quote to payment and final creation. Notable gaps include lack of update or cancel booking operations, but the core flow is well covered.