The workspace's ideal customer rules (roles, industries, company size, locations, exclusions) and the High-intent and automatic delivery settings.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "get_ideal_customer"
}
}| 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?
The annotations already establish that this is a read-only, idempotent, non-destructive, non-open-world operation. The description adds useful context by listing the categories of returned data, but it does not discuss permissions, rate limits, or other behavioral traits beyond what the annotations cover.
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 a single, front-loaded sentence that efficiently lists the resource contents with no filler. Every phrase earns its place.
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 input parameters, rich annotations, and no output schema, the description sufficiently explains what data is returned. It could be slightly more complete by mentioning the response structure or how the data should be used, but it covers the essential scope.
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?
This tool takes no parameters, so the baseline is 4. The description does not need to explain parameter semantics, and it correctly focuses on the returned resource content instead.
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 identifies the resource—the workspace's ideal customer rules and delivery settings—and enumerates its components (roles, industries, company size, locations, exclusions, High-intent and automatic delivery settings). It lacks an explicit verb like 'get' or 'list', but the resource is specific enough for an agent to understand what the tool retrieves.
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 provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, when-not-to-use cases, or any related sibling tools, leaving usage entirely to inference.
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.