list_agentsList all available expert agents with their roles, domains, and specialties.
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_agents"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| domain | No | Filter agents by domain (e.g., 'finance', 'technology', 'healthcare') |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -{
- "additionalProperties": false,
- "properties": {
- "text": {
- "type": "string"
- }
- },
- "required": [
- "text"
- ],
- "type": "object"
-}New value: +nullDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds the output content (roles, domains, specialties) and the optional domain filter, but doesn't disclose additional behavioral nuances like pagination or default ordering. Given strong annotations, a 3 is appropriate.
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 states the purpose and output fields without excess. Every word contributes value, and it is appropriately concise for the tool's 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?
For a simple list tool with one optional filter and rich annotations, the description covers the output fields and scope. Pagination or return format details are not mentioned, but these are typically expected for list operations and not critical for correct invocation.
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 only parameter 'domain' is fully described in the schema with examples, achieving 100% schema coverage. The tool description adds no further parameter semantics beyond what the schema already provides, so the baseline 3 applies.
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 states a specific verb ('List'), the resource ('expert agents'), and the scope ('all available') along with the fields returned (roles, domains, specialties). It clearly differentiates from get_agent_detail by implying plurality, though it doesn't explicitly name the sibling or contrast with it.
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?
No guidance is given on when to use this tool versus get_agent_detail or other list tools. The description doesn't mention alternatives, exclusions, or context for selection, leaving the agent to infer that list is for overview and detail for specifics.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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