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madmickstar

mcp-eveng

by madmickstar

add_lab_node

Add a network device node to an EVE-NG lab canvas by searching for a template by name or vendor. Automatically resolves the correct template, applies its default settings, and auto-places the node when no position is provided.

Instructions

Add a node to a lab's canvas, resolving the template by search and auto-placing it.

template is a case-insensitive substring search against every template's id, name, and (best-effort) vendor -- not an exact id. Empty matches everything (lists them all); no matches cancels; exactly one match proceeds directly; more than one match lists them and asks you to call again with selection set to the number or exact id/name of the one you want.

Once resolved, fetches the template's own defaults (node type, RAM, CPU, ethernet count, console type, icon, and every other field it reports, e.g. QEMU-specific ones) and uses them for anything you didn't specify -- this works the same way for every vendor's templates. If the template has more than one image and you didn't specify image, this returns the list of images (status "selection_required") and asks you to pick one instead of guessing; with exactly one image, it proceeds directly.

Canvas position auto-places when not given: left to right, 5 nodes per row, 100 units apart starting at (100, 100), wrapping to a new row 100 below; skips any grid slot within 50 units of an existing node on both axes.

Args: lab_path: Full path to the .unl lab file. template: Template id, name, or vendor to search for -- a fragment is enough, e.g. "vios", "cisco", or "juniper". Empty lists every available template. selection: When multiple templates matched, the number or exact id/name of the one to use. node_type: "qemu", "dynamips", or "iol". Defaults to the template's own type. name: Node display name. Defaults to the template's name/prefix. image: Image filename from get_node_template. Required if the template has more than one image; auto-filled if it has exactly one. config: "Unconfigured" or "Saved". left: Exact canvas position from the left, e.g. "100". Auto-placed if omitted. top: Exact canvas position from the top, e.g. "100". Auto-placed if omitted. ram: RAM in MB. Defaults to the template's default. console: "telnet" or "vnc". Defaults to the template's default. cpu: Number of vCPUs. Defaults to the template's default. ethernet: Number of ethernet interfaces/portgroups. Defaults to the template's default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cpuNo
ramNo
topNo
leftNo
nameNo
imageNo
configNoUnconfigured
consoleNo
ethernetNo
lab_pathYes
templateNo
node_typeNo
selectionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

The description discloses critical behavioral traits: auto-placement algorithm (left-to-right, 5 per row, 100-unit spacing, skips occupied slots), template defaulting behavior for unspecified fields, and the special image selection requirement. Since no annotations are provided, the description carries the full burden, and it does so comprehensively, with only minor gaps (e.g., no mention of whether the lab must be open first or if there are write permission requirements).

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 a front-loaded summary paragraph, followed by clear sections for template resolution logic, auto-placement algorithm, and parameter documentation. While it's on the longer side, every sentence adds distinct value. Could be slightly tightened (e.g., 'this works the same way for every vendor's templates' is somewhat redundant), but overall efficient for the complexity.

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 13 parameters (1 required), no annotations, and an output schema (which the description doesn't need to document), the description thoroughly covers the tool's behavior, template resolution workflow, auto-placement, and all parameter semantics. Minor gaps: no explicit mention of error states beyond 'no matches cancels', and no note on whether the lab must be pre-opened. Still, very complete for a complex tool.

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?

Schema description coverage is 0%, meaning the schema provides no descriptions for any of the 13 parameters. The description compensates fully by explaining every parameter in detail: 'template' as substring search, 'selection' for disambiguation, 'node_type' defaults, 'name' defaults, 'image' auto-fill behavior, 'config' and 'console' defaults, canvas position auto-placement logic, and RAM/CPU/ethernet defaulting to template values. This is excellent semantic documentation.

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 begins with a clear verb+resource statement: 'Add a node to a lab's canvas', and specifies two key behaviors (template resolution by search, auto-placement). This distinguishes it from siblings like 'edit_lab_node', 'delete_lab_node', or 'list_lab_nodes' which cover different node operations.

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 a detailed, step-by-step guide for using the tool: explains the template search behavior (case-insensitive substring match, edge cases for empty, no matches, exactly one match, multiple matches requiring selection), and when 'image' must be explicitly provided ('if the template has more than one image'). This gives explicit context for when and how to use the tool effectively.

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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