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build_range_from_skeleton

Create customized cyber range configurations by starting with predefined skeleton templates and modifying them with specific VMs, domains, and SIEM options for security testing environments.

Instructions

Build a complete range configuration starting from a skeleton.

Combines the power of skeleton templates with custom modifications. Start with a base skeleton and add/remove VMs as needed.

Args: skeleton_name: Base skeleton ("basic-ad", "enterprise-ad", etc.) add_vms: List of VM skeleton names to add (e.g., ["sql-server", "exchange"]) remove_vms: List of VM hostnames to remove domain: Custom domain name for AD labs siem_type: SIEM type (wazuh, splunk, elastic) include_siem: Whether to include SIEM include_attacker: Whether to include attacker VM

Returns: Complete customized range configuration

Example: # Start with basic AD and add more servers config = await build_range_from_skeleton( skeleton_name="basic-ad", add_vms=["sql-server", "file-server", "ca"], domain="mycorp.local", siem_type="splunk" )

# Enterprise AD without Exchange
config = await build_range_from_skeleton(
    skeleton_name="enterprise-ad",
    remove_vms=["ex01"]
)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skeleton_nameYes
add_vmsNo
remove_vmsNo
domainNo
siem_typeNowazuh
include_siemNo
include_attackerNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It describes the tool's behavior as building a range configuration with customization options, but lacks details on permissions, rate limits, side effects, or output format. The examples show usage but do not fully disclose behavioral traits like whether this is a read-only or destructive operation, which is a gap for a tool with no annotations.

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 well-structured and front-loaded: it starts with a clear purpose, followed by usage context, detailed parameter explanations, return value, and practical examples. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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?

Given the complexity (7 parameters, no annotations, no output schema), the description does a good job covering purpose, usage, and parameters. However, it lacks details on behavioral aspects like error handling or security requirements, and the output is only vaguely described as 'Complete customized range configuration' without schema. This leaves some gaps for full contextual understanding.

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 provides a detailed 'Args' section explaining each parameter's purpose with examples, such as 'skeleton_name: Base skeleton' and 'add_vms: List of VM skeleton names to add.' This adds significant meaning beyond the bare schema, though it does not cover all nuances like default values or constraints, keeping it from a perfect score.

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: 'Build a complete range configuration starting from a skeleton' and 'Combines the power of skeleton templates with custom modifications.' It specifies the verb ('build'), resource ('range configuration'), and method ('from a skeleton'), and distinguishes it from siblings like 'build_range_from_description' or 'build_range_from_scratch' by focusing on skeleton-based customization.

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: 'Start with a base skeleton and add/remove VMs as needed.' It implies usage for customizing pre-defined skeletons rather than building from scratch or description. However, it does not explicitly state when not to use it or name specific alternatives among siblings, which prevents a perfect score.

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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