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zcell_list_anomaly_policy_violations

Read-only

Lists ICCIDs that violated a Zscaler Cellular anomaly policy. Provides violation data over a configurable lookback period.

Instructions

List the ICCIDs that violated a Zscaler Cellular anomaly policy.

Read-only. Returns the policy rows carrying violation data over a days lookback window. Use zcell_list_iccid_violations to drill into the per-event detail for a specific ICCID.

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.
policy_idYes
Behavior4/5

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

Annotations already include 'readOnlyHint: true', but the description adds that the tool returns 'policy rows carrying violation data over a `days` lookback window', which provides temporal scope. No contradictions; the description adds useful behavioral context beyond the annotation.

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 three concise sentences: the first states the main action, the second notes read-only, and the third points to the sibling tool. There is 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?

Given 5 parameters and no output schema, the description covers the core purpose and one parameter hint but fails to explain pagination ('page', 'size'), the optional 'query' filter, or the return structure. It is adequate but has clear gaps.

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?

The input schema has 5 parameters with only 20% description coverage (only 'query' has a description). The tool description only hints at the 'days' parameter via 'over a `days` lookback window', ignoring 'page', 'size', and 'policy_id' (though required). It does not compensate for the low schema coverage.

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 verb 'list' and the resource 'ICCIDs that violated a Zscaler Cellular anomaly policy'. It also distinguishes from the sibling tool 'zcell_list_iccid_violations' by mentioning that the sibling drills into per-event detail, making the purpose specific and differentiated.

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 explicitly says 'Read-only.' and provides a clear alternative: 'Use `zcell_list_iccid_violations` to drill into the per-event detail for a specific ICCID.' This gives context for when to use this tool vs the sibling, though it doesn't outline exclusions for other scenarios.

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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