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suggest_range_enhancements

Enhance cyber range configurations by suggesting additional components, capabilities, and improvements to increase realism, educational value, or alignment with specific training goals.

Instructions

Suggest enhancements to improve a range configuration.

Given a basic range description, this tool suggests additional components, capabilities, and improvements to make the range more realistic, educational, or aligned with specific training goals.

Args: current_description: The current range description or configuration intent enhancement_focus: What to focus on for enhancements Options: "comprehensive", "realism", "security", "learning", "performance"

Returns: Dictionary with: - original_config: Parsed understanding of current description - suggested_additions: New VMs, services, or capabilities to add - configuration_improvements: Better network topology, resource allocation - learning_enhancements: Additional training scenarios enabled - implementation_notes: How to implement the suggestions

Examples: # Enhance basic AD lab result = await suggest_range_enhancements( "Simple AD lab with DC and 2 workstations", enhancement_focus="comprehensive" ) # Might suggest: file server, SQL server, SIEM, attacker VM, etc.

# Make lab more realistic
result = await suggest_range_enhancements(
    "Red team lab with AD and Kali",
    enhancement_focus="realism"
)
# Might suggest: multiple DCs, realistic AD misconfigs, segmentation

# Focus on learning value
result = await suggest_range_enhancements(
    "Web app testing lab",
    enhancement_focus="learning"
)
# Might suggest: vulnerable apps, varied web servers, WAF bypass scenarios

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
current_descriptionYes
enhancement_focusNocomprehensive
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the tool as a suggestion generator ('suggests enhancements'), which implies it is non-destructive and likely read-only, but does not explicitly state safety, permissions, or rate limits. The examples add context about output structure, but behavioral traits like idempotency or error handling are not covered.

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 well-structured and front-loaded with the purpose, followed by parameter explanations and examples. It is appropriately sized with no redundant sentences, though the examples section is lengthy but useful for clarity. Every sentence adds value, such as distinguishing enhancement focuses.

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 complexity of a 2-parameter tool with no annotations and no output schema, the description is moderately complete. It covers purpose, parameters, and output structure via examples, but lacks explicit details on error conditions, limitations, or integration with sibling tools like 'build_range_from_description'. The output is described in the examples, but not formally in an output schema.

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?

Schema description coverage is 0%, so the description must compensate. It explains both parameters: 'current_description' as 'The current range description or configuration intent' and 'enhancement_focus' with its options and purpose ('What to focus on for enhancements'). This adds significant meaning beyond the bare schema, though it could detail format constraints for 'current_description'.

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 purpose: 'Suggest enhancements to improve a range configuration.' It specifies the verb ('suggest enhancements') and resource ('range configuration'), and distinguishes itself from sibling tools like 'build_range_from_description' or 'optimize_resource_allocation' by focusing on enhancement recommendations rather than creation or optimization.

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 context for when to use this tool: 'Given a basic range description, this tool suggests additional components, capabilities, and improvements.' It implies usage for enhancing existing configurations but does not explicitly state when not to use it or name specific alternatives among siblings, such as 'optimize_resource_allocation' for performance tuning.

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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