axiorank_list_agentsList the active agents in your AxioRank workspace (id, name, labels, quarantine + last-used status). Use this to find an agent's id before calling agent-specific tools. Requires the agents:read scope.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds meaningful context by specifying the required `agents:read` scope and the exact set of fields returned (id, name, labels, quarantine, last-used status), which is not evident from annotations alone.
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 two sentences, front-loads the action and result, then provides usage guidance and scope. Every sentence is necessary and no fluff. It is perfectly concise and well-structured.
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 no output schema, the description fully explains the return data (id, name, labels, quarantine, last-used status) and required scope. It is complete for a simple list tool with no parameters, covering all necessary information for an AI agent to use it correctly.
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 tool has zero parameters, and schema coverage is 100% (vacuously). According to scoring guidelines, 0 parameters yields a baseline of 4. The description does not need to add parameter information but does mention return fields, which is appropriate for completeness.
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 states it lists active agents in the workspace with specific fields (id, name, labels, quarantine, last-used status). It explicitly states the purpose: to find an agent's ID before calling agent-specific tools, distinguishing it from sibling tools like axiorank_get_agent or axiorank_create_agent.
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 explicitly says 'Use this to find an agent's id before calling agent-specific tools,' providing clear when-to-use guidance. It also implies when not to use (when ID is known) and mentions the required scope, giving comprehensive usage context.
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.
Each tool has a clearly distinct purpose, covering different aspects of agent, policy, incident, and threat management with no overlap. Tools like axiorank_list_agents and axiorank_get_agent are differentiated by list vs. get, and quarantine vs. revoke serve different use cases.
All tools follow a consistent 'axiorank_verb_noun' pattern in snake_case, making it easy to predict tool names based on action and resource. No mixing of conventions or abbreviations.
With 22 tools, the server covers a comprehensive security governance domain. While slightly above the typical 'well-scoped' range, each tool serves a specific function and the count is justified by the breadth of features (agents, policies, incidents, scoring, verification, audit).
The tool surface covers agent and policy lifecycle (CRUD except delete), incident querying, scoring, verification, and audit. Minor gaps include missing delete operations for policies and incidents, and no way to update incident status. However, the core workflows are well-supported.