list_sources
List where the voice AI vendor data comes from, with the license and refresh of each source.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List where the voice AI vendor data comes from, with the license and refresh of each source.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is fully covered. The description adds that each entry carries license and refresh metadata, which is useful context, but says nothing about result size, pagination, or whether the list is static.
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 with no filler. The phrasing 'refresh of each source' is slightly ambiguous (refresh cadence vs. last-refreshed timestamp) but costs little.
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?
With no parameters and no output schema, the definition's job is to tell the agent what comes back, and it does (source, license, refresh info). A word on result shape or whether entries are stable would make it fully 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 tool takes zero parameters, so there is no parameter semantics to explain; baseline 4 applies. The description correctly does not invent parameters.
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?
States a specific verb (list) and resource (sources of voice AI vendor data) and previews the fields returned (license, refresh). It is distinguishable from siblings like list_categories or list_places, though it never names them or draws an explicit boundary.
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?
Usage is only implied: this is the tool for provenance/licensing questions. There is no explicit when-to-use, when-not-to-use, or pointer to an alternative tool for related lookups.
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.