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by zscaler

zms_list_agents

Read-only

List ZMS microsegmentation agents and retrieve details like connection status, version, OS, and IP. Use the returned eyez_id for agent-group or nonce operations.

Instructions

List ZMS microsegmentation agents.

Read-only. Returns one row per agent (eyez_id, name, connection status, version, OS, IP). Requires ZSCALER_CUSTOMER_ID. Use a returned eyez_id with the agent-group / nonce tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
sortNo
queryNoOptional JMESPath expression applied to the results after the API call, for client-side filtering and projection. Field names are exactly what the Zscaler API returns. Examples: "[?enabled==`true`]", "[*].{name: name, id: id}", "length(@)". Omit to get the full records.
searchNo
sort_dirNo
page_sizeNo
Behavior3/5

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

Annotations already declare readOnlyHint=true. The description reiterates 'Read-only' and adds that it returns one row per agent, but does not disclose additional behavioral traits such as pagination, rate limits, or side effects. Given the annotations cover safety, the description adds minimal value beyond confirming read-only nature.

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?

The description is concise at 4 sentences, front-loaded with the main purpose. Every sentence adds value: the action, read-only nature, output fields, requirement, and downstream usage hint. No wasted words.

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?

The tool has 6 parameters and no output schema, yet the description adequately covers the high-level purpose, output structure, and how to use results with sibling tools. It could be more complete by summarizing parameter behavior, but for a list tool with annotations, it is mostly sufficient.

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

Parameters2/5

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

Schema description coverage is only 17% (only 'query' parameter has a description). The tool description does not explain any of the 6 parameters, leaving agents to rely solely on the sparse schema. This under-compensates for low coverage, as the description should have provided parameter 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 'List ZMS microsegmentation agents' with specific verb and resource. It also lists key output fields (eyez_id, name, connection status, version, OS, IP) and hints at related tools (agent-group / nonce), distinguishing it from siblings in the same domain.

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 calls out 'Read-only' and 'Requires ZSCALER_CUSTOMER_ID'. It advises using a returned `eyez_id` with agent-group and nonce tools, which provides context on downstream usage. However, it does not explicitly state when not to use this tool or compare it to alternatives.

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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