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List Virtual_machines

netbox_list_virtual_machines
Read-onlyIdempotent

List virtual machines from your NetBox inventory with pagination and filters for name, status, cluster, role, tenant, and date ranges.

Instructions

List virtual machines from NetBox.

Supports pagination and filtering. Common patterns:

  • Discovery: call with no filters to browse the first virtual_machines.

  • Lookup by id: use netbox_get_virtual_machine instead when you already have an id.

  • Narrow scan: combine 'q' (fuzzy text) with resource-specific filters below.

Pagination:

  • 'limit' (max 1000, default 50) and 'offset'. Response includes 'has_more' and 'next_offset'.

  • Large list responses auto-truncate to keep under the character limit; keep calling with next_offset to continue.

Resource-specific filters:

  • name:

  • cluster_id:

  • status:

  • role_id:

  • tenant_id:

Universal filters:

  • q (string) Fuzzy text search across searchable fields.

  • tag (string[]) AND-filter by tag slugs.

  • created_after (date) ISO-8601 lower bound on 'created'.

  • created_before (date) ISO-8601 upper bound on 'created'.

Returns: Markdown summary (default) or JSON with shape: { total, count, offset, limit, items: [...], has_more, next_offset? }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFuzzy full-text search across the object's searchable fields (name, description, etc.).
tagNoFilter to objects that have ALL of these tag slugs. Repeat for multiple tags (AND semantics in NetBox).
nameNo
limitNoMaximum number of items to return per page (1-1000, default 50).
offsetNoNumber of items to skip for pagination. Use next_offset from a previous response.
statusNo
role_idNo
tenant_idNo
cluster_idNo
created_afterNoISO-8601 date; only return objects created on or after this date (e.g. 2024-01-01).
created_beforeNoISO-8601 date; only return objects created on or before this date.
response_formatNoOutput format: 'markdown' (default, human-readable) or 'json' (full structured payload). Use 'json' when chaining follow-up tool calls.markdown
Behavior5/5

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

The description adds significant behavioral context beyond annotations: pagination auto-truncation, use of next_offset, response shape, and handling of large lists. No contradiction with annotations (readOnlyHint, idempotentHint, etc.).

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 with sections (common patterns, pagination, filters, return format). It is concise yet comprehensive, with no wasted sentences.

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 no output schema, the description thoroughly explains the return format (Markdown or JSON with shape { total, count, offset, limit, items, has_more, next_offset? }). It covers all essential aspects: pagination, filtering, and output options.

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?

The description lists resource-specific and universal filters, including explanation of 'q', 'tag', 'created_after', 'created_before'. Some parameters like 'name' have no schema description, but the description lists them. With 58% schema coverage, the description compensates by grouping and explaining, though individual parameter semantics for some (e.g., 'cluster_id') are not elaborated.

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 explicitly states 'List virtual machines from NetBox' and provides clear patterns (discovery, lookup by id, narrow scan). It directly distinguishes from the sibling tool netbox_get_virtual_machine, making the purpose unambiguous.

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 when-to-use guidance (e.g., 'use netbox_get_virtual_machine instead when you already have an id') and common patterns like 'Discovery: call with no filters'. This helps the agent choose the correct tool for the context.

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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