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get_range_skeleton

Generate pre-configured cyber range environments for security testing, including AD labs, red team exercises, and malware analysis with customizable VMs and network rules.

Instructions

Get a complete range skeleton configuration.

Retrieves a fully-configured range skeleton with all VMs and network rules. Some skeletons support additional customization parameters.

Args: name: Skeleton name (e.g., "basic-ad", "enterprise-ad", "red-team") domain: Custom domain name (for AD labs, default: "yourcompany.local") workstations: Number of workstations (for basic-ad, default: 2) include_attacker: Include Kali attacker VM (default: True) include_siem: Include SIEM monitoring (default: True) siem_type: SIEM type: "wazuh", "splunk", "elastic" (default: "wazuh")

Returns: Complete range configuration with VMs and network rules

Available skeletons: - basic-ad: Customizable with domain, workstations, attacker, siem - enterprise-ad: Full enterprise with CA, file server, SQL, exchange - red-team: DMZ + internal AD for red team exercises - soc-training: Monitored endpoints for SOC training - web-pentest: DVWA, Juice Shop, WebGoat - malware-analysis: Isolated RE lab

Example: # Get a basic AD lab config = await get_range_skeleton("basic-ad")

# Get a customized AD lab
config = await get_range_skeleton(
    "basic-ad",
    domain="corp.local",
    workstations=4,
    siem_type="splunk"
)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
domainNo
workstationsNo
include_attackerNo
include_siemNo
siem_typeNowazuh
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 discloses that the tool retrieves configurations, implying a read-only operation, and mentions customization parameters, but lacks details on behavioral traits like error handling, performance, or side effects. The description does not contradict annotations, but it could be more informative about what 'complete range skeleton' entails in practice.

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 with clear sections (purpose, args, returns, available skeletons, example) and uses bullet points for readability. It is appropriately sized, but some redundancy exists (e.g., repeating skeleton names in the 'Available skeletons' list after mentioning them earlier). Every sentence adds value, though it could be slightly more front-loaded.

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 (6 parameters, no annotations, no output schema), the description is quite complete. It covers purpose, parameters with semantics, return values, available skeletons, and examples. However, it lacks details on output format or potential errors, and with no output schema, more information on the return structure would be beneficial for full completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by providing detailed semantics for all 6 parameters. It explains each parameter's purpose, gives examples (e.g., 'name: Skeleton name (e.g., "basic-ad", "enterprise-ad", "red-team")'), lists defaults, and clarifies usage for specific skeletons, adding significant value beyond the bare schema.

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: 'Get a complete range skeleton configuration' and 'Retrieves a fully-configured range skeleton with all VMs and network rules.' It specifies the verb ('Get', 'Retrieves') and resource ('range skeleton configuration'), and distinguishes from siblings by focusing on pre-configured skeletons rather than building from scratch or other methods.

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 by listing available skeletons (e.g., 'basic-ad', 'enterprise-ad', 'red-team') and noting that 'Some skeletons support additional customization parameters.' However, it does not explicitly state when NOT to use it or name specific alternatives among the many sibling tools, such as 'build_range_from_skeleton' or 'get_range_config', which might be relevant.

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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