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Metrx MCP Server

by metrxbots

List Agents

metrx_list_agents
Read-onlyIdempotent

Retrieve a list of all AI agents in your organization, including status, category, and cost. Optionally filter by status or category to obtain agent IDs for use with other tools.

Instructions

List all AI agents in your organization with their status, category, and cost. Optionally filter by status or category. Returns agent IDs needed for other tools. Do NOT use for detailed per-agent analysis — use get_agent_detail for that.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoFilter by agent status
categoryNoFilter by agent category (e.g., "sales", "support", "engineering")
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description does not need to repeat safety. However, it adds valuable context that the tool 'Returns agent IDs needed for other tools', which informs the agent about how the output may be used downstream.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no unnecessary words. The key information (what the tool does and when to avoid it) is front-loaded. Every sentence serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool with two optional parameters and no output schema, the description covers everything needed: what is returned, that IDs can be used elsewhere, and the boundary with the detail tool. Annotations handle safety and idempotency.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% (both parameters have descriptions). The description merely reiterates that filtering is optional ('Optionally filter by status or category') without adding new meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('List') and resource ('AI agents'), and clarifies what data is returned (status, category, cost). It also distinguishes from the sibling tool 'get_agent_detail' by stating that this is for listing, not detailed analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when not to use this tool ('Do NOT use for detailed per-agent analysis') and provides a clear alternative ('use get_agent_detail for that'). This helps the agent select the correct tool.

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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