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by zscaler

get_zia_dlp_engines

Read-only

Read ZIA DLP engines: list all/lite, or fetch one by ID (read-only).

Instructions

Read ZIA DLP engines: list all/lite, or fetch one by ID (read-only).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoOptional JMESPath expression applied to the results after the API call, for client-side filtering and projection. Examples: "[?enabled==`true`]", "[*].{name: name, id: id}", "length(@)". Omit to get the full records. IMPORTANT: field names are the keys of the returned records, which are usually snake_case (`custom_category`) even where the Zscaler API documents camelCase (`customCategory`) — guessing the spelling yields an empty list that looks like a real answer. If you have not already seen a record from this tool, call it once without `query` and read the keys off the response.
actionNoread
searchNo
engine_idNo
Install Server

TDQS

A3.9/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true and openWorldHint=false, so the description's 'read-only' phrasing is consistent and not contradictory. It adds behavioral context about listing vs fetching by ID, but does not explain what 'lite' means or describe the shape of results. This is acceptable but not rich, especially with no output schema.

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 a single, front-loaded sentence that communicates the core purpose and modes without wasting words. Every phrase earns its place.

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

Completeness3/5

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

For a simple read-only tool with four parameters and no output schema, the description covers the main entry points but does not explain the 'lite' variant, the search parameter, or return format. The query parameter's schema description adds important caveats, so the overall package is workable but incomplete for an agent needing to use all available options effectively.

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 schema describes only the query parameter (25% coverage), so the description carries more burden. It clarifies the action parameter ('list all/lite') and engine_id ('fetch one by ID'), but completely omits the search parameter. The query parameter's detailed schema description compensates partially, but the search parameter remains unexplained, leaving a meaningful gap.

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 ('Read'), names the resource ('ZIA DLP engines'), and clearly distinguishes the two modes: list all/lite or fetch one by ID. It is distinct from sibling tools like get_zia_dlp_dictionaries by naming a different resource.

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 provides clear context for when to use the tool and when to use its internal modes ('list all/lite' vs 'fetch one by ID'). It does not explicitly name alternative tools for DLP dictionaries, but the sibling list makes this less critical. No exclusions or alternative tools are mentioned, so it falls just short of a 5.

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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