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sentinelone-mcp

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Get Storyline Events

get_storyline_events

Fetch Deep Visibility events for a given storyline, using S1QL filters to isolate URLs or process creations for security investigation.

Instructions

Fetch Deep Visibility events for a storyline (Management API). Use event_filter for S1QL: ObjectType = "URL" for URLs, event.type = "Process Creation" for processes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
tenantNo
to_dateNo
from_dateNo
storylineYes
event_filterNo
timeout_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It only describes the high-level fetch action and filter syntax; it does not disclose pagination, result limits, date/time semantics, authentication requirements, or any other behavioral traits.

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?

Two sentences with no filler: the first states the operation and scope, the second provides actionable filter examples. Every sentence earns its place.

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?

For a 7-parameter tool with no annotations, the description is under-specified. It does not explain date range behavior, tenant override, limit, timeout, or how to obtain a storyline ID; the output schema reduces the need to describe return values but does not fill these operational 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?

Schema description coverage is 0%, and the description only adds meaning for event_filter through S1QL examples. The other six parameters (limit, tenant, to_date, from_date, timeout_seconds) are left unexplained, so the description 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.

Purpose4/5

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

The description uses a specific verb and resource ('Fetch Deep Visibility events for a storyline') and adds the Management API context. This clearly identifies the tool's purpose, though it does not explicitly contrast it with siblings like run_dv_query or xdr_query.

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?

It gives practical usage guidance by telling the agent to use event_filter with S1QL and provides concrete examples for URLs and processes. However, it never states when to prefer this tool over alternative query tools; the selection logic is only implied by 'for a storyline.'

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.