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BorealHost

by ai.borealhost

list_compute_volumes

List your compute volumes — machines that survive instance termination.

A volume is a whole machine (packages, drivers, services, users, data) stored in Canada. Detaching destroys the instance but keeps the machine; attaching restores it onto a fresh instance, optionally of a DIFFERENT type. That is how you move a workload from a small CPU box to a big GPU box without rebuilding it.

Requires: API key with read scope.

Returns: {"volumes": [{"id", "name", "state", "instance_type", "stored_gb", "has_snapshot", "instance": {...} or null}, ...], "price_cad_per_gb_month": 0.03}

state is one of: creating, attached, detaching, detached, attaching,
error. Only "attached" has a running instance you can log into.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description fully discloses the tool's read-only nature, required scope, and return format including state values and their meanings. It explains the volume lifecycle (detaching keeps machine, attaching restores) and notes pricing. It doesn't mention pagination or rate limits but is transparent about core behavior.

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 concise at ~100 words, front-loading the purpose, then explaining context, requirements, and output format in a logical flow. Each sentence adds necessary information with no redundancy or filler.

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 zero parameters, no output schema, and low complexity, the description fully covers what the agent needs: purpose, behavior, prerequisites, return structure, and state semantics. It compensates for the lack of output schema by explicitly showing the JSON fields.

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?

There are zero parameters, and schema coverage is 100% vacuously. The description adds value by explaining the output structure and state field, which is not present in the schema. This meets the baseline of 4 for zero-parameter tools.

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 lists compute volumes and defines them as machines that survive instance termination, which distinguishes it from sibling tools like list_compute_instances. It gives concrete details about volumes being stored in Canada and their lifecycle (detaching/attaching).

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 explains when to use this tool (to list volumes that persist beyond instances) and provides context about states and requirements (API key with read scope). It implicitly contrasts with instance listing but lacks explicit exclusions or direct comparisons to siblings.

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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TDQS

A3.6/5.0
Disambiguation3/5

Several tools have overlapping boundaries, such as add_domain_dns vs manage_dns for DNS records, create_backup vs create_snapshot vs create_b2_snapshot for saved states, and write_file vs upload_file for file writing. Most tools are distinct, but these near-duplicates require agents to read descriptions carefully to avoid misselection.

Naming Consistency3/5

The naming pattern is mostly consistent verb_noun in snake_case (e.g., list_* , create_*, delete_*), but there are noticeable deviations: 'add' vs 'create' for similar operations, 'delete' vs 'remove', and outliers like manage_dns, whoami, and scale. The overall style is readable but not perfectly uniform.

Tool Count2/5

144 tools is far beyond the 'too many' threshold and would be unwieldy for agents to navigate. While the server covers a broad hosting platform with many distinct resources, the sheer number makes it difficult for each tool to earn its place, and many are simple list/get variants that could be consolidated.

Completeness4/5

The tool surface is remarkably comprehensive, covering site lifecycle, domains/DNS, compute instances/volumes, backups/snapshots, file management, databases, WordPress administration, email, security, monitoring, billing, webhooks, and support. A notable gap is the lack of a direct list_sites tool—agents must infer site slugs from list_subscriptions—but overall the domain is well covered.

Resources