Retrieve all customer records from the Waldur MCP Server to manage client data and access service information.
List all customers
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": "list_customers"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'List all customers' implies a read-only operation but doesn't specify permissions, rate limits, pagination, or output format. For a tool with zero annotation coverage, this is a significant gap in transparency about how it behaves and what to expect.
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 extremely concise with just three words, front-loading the core action and resource without any waste. Every word earns its place by directly stating the tool's purpose, making it efficient and well-structured for its simplicity.
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?
Given the lack of annotations and output schema, the description 'List all customers' is incomplete. It doesn't explain what 'all' entails (e.g., pagination, filters), the return format, or any behavioral constraints. For a tool with no structured data to rely on, this leaves critical gaps in understanding its operation and results.
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 input schema has 0 parameters with 100% description coverage, meaning no parameters need documentation. The description doesn't add parameter details, which is appropriate here. Baseline is 4 for 0 parameters, as the schema fully covers the lack of inputs without requiring compensation from the description.
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 'List all customers' clearly states the verb ('List') and resource ('customers'), providing a basic understanding of the tool's function. However, it lacks specificity about scope or format and doesn't differentiate from sibling tools like 'list_invoices' or 'list_projects' beyond the resource name. This makes it vague rather than specific.
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. There is no mention of context, prerequisites, or exclusions, and it doesn't reference sibling tools like 'query' that might offer overlapping functionality. This leaves the agent with no usage direction beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.