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zcell_list_audit_customers_search

Read-only

Search cellular audit logs over a lookback window to identify changes made by users, with optional filters for operation type, object, and visibility.

Instructions

Search Zscaler Cellular audit-log entries over a lookback window.

Read-only. Returns curated audit rows (who changed what, when, and the operation) over a days window, with optional operation/object/visibility filters. The before/after data blobs are omitted from the row.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
pageNo
sizeNo
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.
object_idNo
visibilityNo
object_nameNo
object_typeNo
operation_typeNo
modified_by_user_idNo
Behavior4/5

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

Annotations already declare readOnlyHint=true. The description adds valuable context: it returns curated rows, omits before/after blobs, and mentions optional filters. No contradiction with annotations.

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 four lines, front-loaded with the core purpose, and every sentence adds necessary detail without redundancy. Highly efficient.

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?

No output schema exists, so the description partially explains returned data (curated rows with who, what, when, operation). However, it is missing details on pagination, error behavior, and full parameter descriptions for a 10-parameter tool. Adequate but not comprehensive.

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?

Schema description coverage is only 10% (one parameter documented). The description mentions operation/object/visibility filters but does not explain days, page, size, object_id, object_name, object_type, modified_by_user_id. It adds partial value but is insufficient for the 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 clearly states the tool searches Zscaler Cellular audit-log entries over a lookback window, specifies it is read-only, and lists the key data returned (who, what, when, operation). It distinguishes itself from siblings by focusing on audit customers.

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

Usage Guidelines3/5

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

The description implies usage for audit log queries but does not explicitly mention when to use this tool vs alternatives or provide exclusions. Sibling tools are many, but no comparative guidance is given.

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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