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deploy_range

Deploy custom cyber range configurations or resume partial deployments using Ansible tags and VM filters for targeted infrastructure setup.

Instructions

Deploy a range from configuration with optional filters for resuming.

IMPORTANT: For deploying predefined scenarios (redteam-lab-lite, etc.), use deploy_scenario() or smart_deploy() instead. This tool is for:

  • Custom configurations you've built manually

  • Resuming partial deployments with tags/limit

  • Deploying after you've already set the config via update_range_config()

This tool supports both full deployments and resuming partial deployments.

Full Deployment: deploy_range(config=configuration_dict)

Resume After Pause/Abort: deploy_range(tags="user,domain") # Run specific Ansible tags only deploy_range(limit="DC*") # Deploy only to matching VMs deploy_range(tags="user", limit="WS*") # Combine filters

Common Ansible Tags: - "base": Base system configuration - "domain": Domain join operations - "user": User creation and management - "configure": General configuration - "testing": Testing configuration Use get_range_tags() to see all available tags for your range

Args: config: Range configuration (required for full deployment, optional for resume) user_id: Optional user ID (admin only) tags: Ansible tags to run (comma-separated, e.g., "user,domain") limit: Limit to VMs matching pattern (e.g., "DC*", "WS*", "*-DC01") only_roles: Limit user-defined roles (comma-separated) force: Force deployment if testing is enabled

Returns: Deployment result

Use Cases: 1. Initial deployment: deploy_range(config=my_config) 2. Resume after abort: deploy_range(tags="user,domain") 3. Re-run specific tags: deploy_range(tags="configure") 4. Fix specific VM: deploy_range(limit="DC01") 5. Update workstations only: deploy_range(limit="WS*", tags="user") 6. After role installation: deploy_range(tags="configure")

Example Workflow - Resume After Failure: 1. abort_range_deployment() # Stop the failed deployment 2. get_range_tags() # See available tags 3. deploy_range(tags="user,domain") # Resume from specific step

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
configNo
user_idNo
tagsNo
limitNo
only_rolesNo
forceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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 does an excellent job describing deployment behaviors: supporting both full deployments and resuming partial deployments, explaining how to use tags and limit filters, mentioning that it can resume after pause/abort, and providing common Ansible tags. However, it doesn't explicitly mention whether this is a read-only or destructive operation, though 'deploy' implies mutation.

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 (full deployment, resume, common tags, args, returns, use cases, workflow) but is quite lengthy. While every section adds value, it could be more concise. The information is front-loaded with the most important guidance first, and the structure helps navigation despite the length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a deployment tool with 6 parameters, 0% schema coverage, no annotations, but with an output schema, the description is remarkably complete. It covers purpose, usage guidelines, parameter semantics, behavioral context, use cases, and workflow examples. The output schema handles return values, so the description appropriately focuses on how to use the tool rather than what it returns.

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 for 6 parameters, the description fully compensates by providing rich semantic information. It explains each parameter's purpose: config (required for full deployment), tags (comma-separated Ansible tags), limit (VM matching pattern), only_roles (limit user-defined roles), force (force deployment if testing enabled), and user_id (admin only). It provides examples, formatting guidance, and usage context that goes far 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: deploying a range from configuration with optional filters for resuming. It distinguishes from siblings by explicitly naming alternatives (deploy_scenario, smart_deploy) and specifying this is for custom configurations, not predefined scenarios. The verb 'deploy' is specific and the resource 'range' is clearly identified.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool versus alternatives, stating 'IMPORTANT: For deploying predefined scenarios... use deploy_scenario() or smart_deploy() instead.' It also clearly defines three specific use cases for this tool and provides detailed examples of when to use different parameter combinations for full vs. resume deployments.

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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