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Space-C0wboy

ReliaQuest GreyMatter MCP Server

by Space-C0wboy

detection_rules

List deployed detection rules across GreyMatter integrations with MITRE ATT&CK mapping, filterable by authors, locations, and IDs to refine results.

Instructions

List deployed detection rules across GreyMatter integrations (includes MITRE ATT&CK mapping where available). Variables: after, detectionRuleOrder, filter, first. Example variables: {"after":"T18w","detectionRuleOrder":{"direction":"ASC","orderBy":"ID"},"filter":{"authors":{"connectorId":"","reliaQuest":true},"deployedLocations":{"connectorId":"","digitalRiskProtection":true,"greymatter":true},"endDate":"2026-05-01T00:00:00.000Z","ids":[""],"killch...

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNoGraphQL: String
firstNoGraphQL: Int
filterNoGraphQL: DetectionRuleFilter
customer_slugNoOverride the x-reliaquest-customer (OpCo) header.
detectionRuleOrderNoGraphQL: DetectionRuleOrder
Behavior3/5

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

Without annotations, the description carries the burden of behavioral disclosure. It notes that MITRE ATT&CK mapping is included "where available," which is useful context about the output. However, it does not mention read-only behavior, pagination defaults, required permissions, or the meaning of "deployed." The example variables hint at filter structure but add only partial transparency.

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 main sentence is concise and front-loaded with the core purpose. The variable list and example are useful but the example is abruptly truncated mid-string, which hurts readability. Overall, it is reasonably concise but lacks polish in the example presentation.

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 has 5 parameters, no output schema, and no annotations, the description should clarify return value structure, pagination behavior, and operational context. It mentions the list includes MITRE mapping and provides a filter example, but it does not explain how pagination works (after/first), what "deployed" means, or what fields are returned. The description is adequate for a basic list call but leaves gaps that the schema and annotations do not fill.

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 descriptions for parameters are unhelpful (just "GraphQL: String", etc.), so the description's example variables add real value by illustrating the structure of filter, detectionRuleOrder, and after. This goes beyond the schema, though the example is truncated and does not fully explain all parameters (e.g., first).

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's function: "List deployed detection rules across GreyMatter integrations (includes MITRE ATT&CK mapping where available)." The verb "List" specifies the action, and the resource and scope are explicit. This distinguishes it from sibling tools like customer_detections, which likely focuses on customer-specific detections.

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 such as customer_detections or detection_rule (singular). It does not mention prerequisites, suitability for specific use cases, or exclusions. The only hint is the word "deployed," implying a focus on active rules, but this is not elaborated.

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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