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CoveoSec
by CoveoSec

audits_management_logs

Retrieve Cortex XSIAM audit management logs with filtering and sorting to analyze user actions and system events.

Instructions

Get Audit Management Log

Get audit management logs.

  • Response is concatenated using AND condition (OR is not supported).

  • Maximum result set size is 100.

  • Offset is the zero-based number of incidents from the start of the result set.

[POST /public_api/v1/audits/management_logs] · Audit log

Example request body:

{
  "request_data": {
    "search_from": 0,
    "search_to": 19,
    "sort": {
      "field": "email",
      "keyword": "ASC"
    },
    "filters": [
      {
        "field": "type",
        "operator": "in",
        "value": [
          "AUTH"
        ]
      },
      {
        "field": "sub_type",
        "operator": "in",
        "value": [
          "login"
        ]
      },
      {
        "field": "result",
        "operator": "in",
        "value": [
          "SUCCESS"
        ]
      },
      {
        "field": "timestamp",
        "operator": "lte",
        "value": 1565074114053
      }
    ]
  }
}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_dataNoA dictionary containing the API request fields. An empty dictionary returns all results.
Behavior3/5

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

With no annotations, the description must reveal behavioral traits. It discloses that responses are concatenated with AND, max result set size is 100, and offset is zero-based. However, it omits permission requirements, error handling, and details about the return format.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a title, bullet points, and an example. It is slightly repetitive ('Get Audit Management Log' appears twice) but each substantive part earns its place, especially the example.

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 the nested request_data object, the schema provides rich detail, and the example further clarifies usage. However, with no output schema, the description does not explain return values or response structure, leaving some context incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already covers 100% of parameters, and the description adds useful semantics: the AND condition, max result set size, and offset behavior. The example request body illustrates how to structure the nested request_data, adding practical value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get audit management logs', specifying the verb and resource. It is distinct from sibling tools like audits_agents_reports, though it does not explicitly highlight what makes management logs unique. The name itself is descriptive enough.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It mentions that OR is not supported and result limits, but gives no context about when this tool is the appropriate choice among audit-related tools.

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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