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zcell_list_network_events

Read-only

Search Zscaler Cellular network/session events over a lookback window.

Instructions

Search Zscaler Cellular network/session events over a lookback window.

Read-only. Returns curated event rows (timestamp, event, outcome, SIM/ICCID, country, carrier, RAT, IP) over a days window, with optional filter_by conditions, sort_by, and pagination.

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. 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.
sort_byNo
filter_byNo
exclude_apn_configNo
Install Server

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already provide readOnlyHint: true, and the description reinforces this with 'Read-only.' It adds behavioral context by stating it returns curated event rows with specific fields, and exposes the lookback window and optional filtering/pagination, which goes beyond annotations. No contradictions.

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 two sentences that front-load the core purpose, then list return fields and parameters. Every sentence adds value with no redundancy or fluff.

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 tool with 7 parameters and no output schema, the description provides a useful summary of returned fields but omits some parameters (exclude_apn_config) and the shape of complex objects. It is not fully complete but covers the essential search/return behavior, making it adequate but not exceptional.

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 coverage is only 14%, so the description must compensate. It adds meaning to 'days' as a lookback window, and mentions filter_by, sort_by, and pagination, but does not explain exclude_apn_config or the structure of sort_by/filter_by objects. The 'query' parameter is well-explained in the schema itself, so partial compensation exists but gaps remain.

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 network/session events over a lookback window, naming a specific verb, resource, and scope. It also lists the curated return fields, distinguishing it from sibling tools like zcell_list_sim_usage_by_sim or zcell_list_anomaly_policies.

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 through 'Search' but provides no explicit when-to-use or when-not-to-use guidance, nor alternatives. With many sibling tools, the lack of differentiation beyond the name leaves the context ambiguous, though the purpose is clear enough to infer basic usage.

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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