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legionultramax

Harris HawkEye MCP

sublime_search

Find email detection rules by keyword, attack type, MITRE technique, or detection method. Get matching rules with severity, category, and MITRE mapping for phishing, BEC, malware, credential theft.

Instructions

Search Sublime Security email detection rules by keyword, attack type, MITRE technique, or detection method. Returns matching rules with severity, category, and MITRE mapping. Use to find email-layer detections for phishing, BEC, malware delivery, and credential theft.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum results to return (default: 20, max: 100)
queryYesSearch term — rule name, attack type (e.g., "credential phishing", "BEC"), MITRE T-ID (e.g., "T1566"), detection method (e.g., "YARA"), or keyword in the MQL source
severityNoOptional: filter by severity level

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral transparency burden. It discloses that the tool searches a rule repository and returns matching rules with severity, category, and MITRE mapping, which implies a read-only search operation. It does not mention limits or edge cases, but for a search tool the core behavior is adequately disclosed.

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 two sentences with no redundancy. It front-loads the primary purpose and search dimensions in the first sentence, then gives the return format and typical use cases in the second. Every sentence contributes useful information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a search tool with 3 parameters and no output schema, the description is largely complete: it names the input dimensions, the result fields, and representative use cases. It does not mention behavior for empty results, pagination, or any access requirements, but these are not critical for selecting and invoking the tool correctly.

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%, so the baseline is 3. The description restates some query semantics such as keyword, attack type, MITRE technique, and detection method, but does not add meaning beyond the schema's parameter descriptions. It does not clarify interactions between query, limit, and severity.

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 specifies the verb 'Search' and the resource 'Sublime Security email detection rules', while listing concrete search dimensions: keyword, attack type, MITRE technique, and detection method. It states the return content (severity, category, MITRE mapping) and is easily distinguishable from sibling tools like sublime_get_rule and search_detections.

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 provides clear usage context: 'Use to find email-layer detections for phishing, BEC, malware delivery, and credential theft.' It does not explicitly name alternative tools or state when not to use it, but the stated use cases are enough for an agent to judge when this tool is appropriate.

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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