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VerifyAX MCP

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List agents

list_agents
Read-only

Retrieve a list of AI agents in your VerifyAX workspace, with options to filter by connector type and paginate results.

Instructions

Lists the AI agents registered in your VerifyAX workspace, optionally filtered by connector type (A2A, API, DIRECTLINE, EXTENSION, or MCP). Returns each agent’s uuid, name, type, and URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
agent_typeNoFilter to a single agent type.
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description aligns by describing a read-only list operation. It adds context on return fields, which is useful. No further behavioral details are needed given the annotation coverage.

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 cover purpose, filtering, and return fields. No redundant information, and the key points are front-loaded. Every part is necessary.

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

Completeness4/5

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

Given low complexity (3 optional params, no output schema), the description covers the main functionality and return fields. Lacks explicit pagination explanation, but the schema parameters imply it. Overall sufficient for the tool.

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?

The description explains the agent_type parameter and its enum values, but does not mention limit or offset parameters. With schema description coverage at 33%, the description partially compensates but could be more complete on pagination context.

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 clearly states the tool lists AI agents in the workspace, with an optional filter by connector type. It specifies the return fields (uuid, name, type, URL), making it distinct from sibling tools like register_agent or delete_scenario.

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

Usage Guidelines4/5

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

The description implies when to use this tool (to list agents, optionally filtered), but does not explicitly provide when-not-to-use or alternatives. It lacks guidance on pagination or cost implications, but the context is clear enough for basic usage.

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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