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legionultramax

Harris HawkEye MCP

get_detection

Retrieve a detection's full details by ID, including query logic, logsource, data sources, CVEs, and false positives, to extract conditions for kill-chain correlation.

Instructions

Get full details of a specific detection by ID. Returns query logic, logsource (product/category/service), data_sources, process_names, platforms, CVEs, and false_positives. Use this to extract detection conditions for kill-chain correlation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesDetection ID

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, the description carries the behavioral disclosure burden. It clearly signals a read-only lookup ('Get', 'Returns') and spells out the exact data returned, so an agent knows what to expect. It does not cover error/not-found behavior, but for a simple getter this is a minor omission rather than a transparency failure.

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, no filler. The first sentence names the operation and resource, the second lists the useful return fields and a concrete use case. Every clause earns its place.

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 one-parameter getter with no output schema and no annotations, the description is nearly complete: it names the input, the output fields, and a use case. Minor omissions such as invalid-ID behavior or output formatting are low-impact for this tool, but would have made it fully complete.

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 coverage is 100% and the only parameter, id, is described as 'Detection ID'. The description reinforces that this ID selects a specific detection but adds no additional format, source, or validation semantics beyond the schema, so it meets the baseline but not more.

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 states a specific verb and resource ('Get full details of a specific detection by ID') and enumerates the returned fields. This makes it clearly distinct from search_detections and the list_by_* siblings, which are about finding detections rather than retrieving a single detection's full record.

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?

It gives a concrete trigger for use: 'Use this to extract detection conditions for kill-chain correlation.' This is clearer than no guidance, but it does not explicitly state when not to use it or name alternatives such as search_detections, so it stops short of a 5.

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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