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vectra-ai-research

Vectra AI MCP Server

list_detections_with_details

Retrieve detailed security threat detections from Vectra AI with filtering by category, state, IP address, date range, and key asset targeting for threat investigation.

Instructions

    List detections with filtering and sorting options. Use this to get a detailed list of detections based on various criteria.

    Returns:
        str: JSON string with list of detections.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orderingNoOrder by last_timestamp, created_datetime, or id. Defaults to ordering by last_timestamplast_timestamp
detection_categoryNoFilter by detection category. Detections are grouped into one of the following categories: Command & Control, Botnet, Exfiltration, Lateral Movement, Reconnaissance, Info. Can also perform partial word match
detection_nameNoFilter by detection name. Can also perform partial word match
stateNoFilter by detection state (active, inactive, fixed, filteredbyai, filteredbyrule). Default is 'active'.active
src_ipNoFilter by source IP address of the host that generated the detection. Must be a valid IPv4 or IPv6 address.
start_dateNoFilter by start date (YYYY-MM-DDTHH:MM:SS)
end_dateNoFilter by end date (YYYY-MM-DDTHH:MM:SS)
is_targeting_key_assetNoFilter for detections targeting a key asset. Defaults to 'False'. Set to 'True' to filter for detections that are targeting key assets. To get all detections regardless of key asset targeting, search for both True and False values.
limitNoMaximum number of detections to return in the batch. Defaults to 1000

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool lists detections with filtering and sorting, but fails to describe critical behaviors such as whether it's read-only (implied but not stated), pagination handling (limit parameter exists but not explained in description), rate limits, authentication requirements, or error conditions. This leaves significant gaps for an agent to understand operational constraints.

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 brief and front-loaded with the core purpose in the first sentence. The second sentence adds context about returns, but the 'Returns:' section is redundant given the output schema exists. Overall, it's efficient with only minor waste, making it easy to parse quickly.

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 tool's complexity (9 parameters, filtering/sorting functionality) and the presence of an output schema, the description is minimally adequate. It states the purpose and return format, but lacks behavioral context (e.g., read-only nature, pagination) and usage differentiation from siblings. With no annotations, it should provide more operational guidance to be fully complete for an agent.

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 100%, meaning all parameters are well-documented in the schema itself. The description adds no specific parameter semantics beyond mentioning 'filtering and sorting options' generically. It does not explain parameter interactions, default behaviors beyond what's in the schema, or usage examples. This meets the baseline for high schema coverage but adds minimal extra value.

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 the tool's purpose as 'List detections with filtering and sorting options' and specifies it returns 'a detailed list of detections based on various criteria.' This distinguishes it from sibling tools like 'list_detection_ids' and 'list_detections_with_basic_info' by emphasizing detailed information and filtering capabilities. However, it doesn't explicitly contrast with these specific siblings.

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 context by mentioning 'filtering and sorting options' and 'various criteria,' suggesting when to use this tool for detailed, filtered lists. However, it lacks explicit guidance on when to choose this over alternatives like 'list_detection_ids' (for IDs only) or 'list_detections_with_basic_info' (for less detail), and does not specify prerequisites or exclusions.

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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