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get_zia_dlp_dictionaries

Read-only

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

Instructions

Read ZIA DLP dictionaries: 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
dict_idNo
Install Server

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint: true, and the description repeats 'read-only,' which is consistent. It adds value by disclosing the two modes (list and fetch by ID) and implies no mutations. However, it does not describe pagination, rate limits, or what 'lite' returns, but for a read tool with annotations, this is adequate.

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 sentence that conveys the core purpose and two modes with zero waste. It is front-loaded and succinct, earning high marks for efficiency.

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

Completeness2/5

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

Given 4 parameters, no output schema, and minimal annotations, the description is too sparse. It omits the 'search' parameter entirely and does not clarify the semantics of 'read_lite' vs 'read'. While the query parameter has a detailed schema description, the other three parameters remain ambiguous. The description does not provide enough context for an agent to confidently use all parameters correctly.

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 25% (only query is described). The tool description barely addresses parameters: it implies action (list all/lite) and dict_id (fetch by ID) but omits 'search' entirely and does not explain the difference between 'read' and 'read_lite'. With three undocumented parameters, the description should provide more semantic context, but it does not.

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 'Read ZIA DLP dictionaries' with specific verbs (list, fetch) and resource. It distinguishes the two modes: list all/lite or fetch by ID. No sibling tool covers DLP dictionaries, so it stands out. The read-only note reinforces the intent.

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 usage: list all/lite for general enumeration or fetch by ID for a specific dictionary. It does not explicitly mention alternatives or when not to use it, but given its uniqueness among siblings, context is clear. It lacks explicit guidance on conditions for choosing 'read' vs 'read_lite'.

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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