list_capabilitiesList every task type this service performs, with evidence returned, price range and turnaround. Call this first when you do not know what can be requested.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful context about the content returned (evidence, price, turnaround), but does not disclose potential pagination or ordering behaviors. No contradiction with 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 two sentences with no wasted words. The first sentence states the primary function and output fields; the second provides usage guidance. Excellent front-loading.
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 zero-parameter, read-only listing tool, the description is complete: it states what is returned, when to use it, and implies it is a discovery entry point. It could mention potential service-area constraints, but those are covered by sibling tools.
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 tool has zero parameters, so the baseline is 4. The description does not need to explain parameters, and there is no schema ambiguity to resolve.
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 a specific verb ('List every task type') and identifies the resource ('this service performs') with concrete output fields (evidence, price range, turnaround). It is clear and distinct from quote_task or submit_request, though it does not explicitly differentiate from the sibling get_use_cases.
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 gives explicit guidance: 'Call this first when you do not know what can be requested.' This provides a clear context for use, but it does not mention when not to use it or describe alternatives.
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.
Most tools have clearly distinct purposes, but get_use_cases and list_capabilities both describe service offerings, creating mild ambiguity about which to call. check_service_area and quote_task also overlap slightly on eligibility checks.
All tool names follow a consistent verb_noun snake_case pattern (check_, get_, list_, quote_, submit_), making the set highly predictable and readable.
Five tools is well within the ideal range and each covers a distinct step in the enquiry workflow, from eligibility check to submission, without unnecessary bloat.
The enquiry lifecycle is well covered: eligibility, capabilities, examples, quoting, and submission. However, there is no tool to track or manage a submitted enquiry, which is a minor gap.