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legionultramax

Harris HawkEye MCP

get_coverage_summary

Retrieve tactic-level detection counts as a compact summary to quickly orient detection coverage before deeper analysis. Optionally filter by source.

Instructions

Get tactic-level detection counts as a compact object (~200 bytes). Faster and smaller than analyze_coverage. Use for quick orientation before deeper analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
source_typeNoOptional: filter by source (sigma, splunk_escu, elastic, kql)

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 disclosure burden. It adds useful behavioral context: the response is a compact object of roughly 200 bytes and the tool is faster/smaller than analyze_coverage, implying a read-only summary operation. It does not detail error behavior or exact output keys, but for a simple read-only summary this is reasonably transparent.

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 three short, purposeful sentences with no filler. It front-loads what the tool does, then adds size/performance characteristics and a usage recommendation. Every sentence 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?

This is a low-complexity tool with one optional parameter and no output schema or annotations. The description sufficiently conveys purpose, output size, and when to use it. However, because no output schema exists and the description only says 'compact object (~200 bytes)', the exact response shape is left somewhat approximate.

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%: the source_type property is already documented with its allowed values (sigma, splunk_escu, elastic, kql). The description does not add any extra parameter semantics, so the baseline score of 3 applies.

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 opens with a specific verb and resource: 'Get tactic-level detection counts as a compact object'. It clearly scopes the tool to tactic-level summary counts and explicitly contrasts it with analyze_coverage as a faster/smaller alternative, making it easy to distinguish.

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 names analyze_coverage as a sibling alternative and positions this tool as the quick-orientation option: 'Use for quick orientation before deeper analysis.' This implies when to choose it, though it does not explicitly spell out when-not-to-use it or what conditions should trigger analyze_coverage instead.

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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