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volume_list

List all persistent storage volumes in a Railway project to view configurations, manage data volumes, and audit storage usage.

Instructions

[API] List all volumes in a project

⚡️ Best for: ✓ Viewing persistent storage configurations ✓ Managing data volumes ✓ Auditing storage usage

→ Prerequisites: project_list

→ Next steps: volume_create

→ Related: service_info, database_deploy

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesID of the project to list volumes for
Behavior3/5

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 indicates this is a listing/read operation ('List all volumes') but doesn't specify whether it returns all volumes at once or uses pagination, what format the output takes, or any rate limits. The description adds some context about storage configurations but leaves important behavioral aspects unspecified.

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 and front-loaded with the core purpose, followed by organized sections (Best for, Prerequisites, Next steps, Related). Every element serves a clear purpose with no wasted words, making it highly efficient and scannable.

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?

For a single-parameter read operation with no output schema, the description provides strong contextual completeness. It covers purpose, usage scenarios, prerequisites, and related tools. The main gap is the lack of output format information, which would be helpful since there's no output schema, but the description otherwise gives good context for agent decision-making.

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

Parameters3/5

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

The schema has 100% description coverage (projectId parameter is fully documented), so the baseline is 3. The description doesn't add any parameter-specific information beyond what's in the schema, but it doesn't need to since the schema already provides complete parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List all volumes') and resource ('in a project'), making the purpose immediately understandable. However, it doesn't differentiate this tool from other volume-related siblings like volume_create or volume_delete, which would require more specific scope definition.

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 excellent usage guidance with explicit 'Best for' scenarios (viewing configurations, managing volumes, auditing usage), clear prerequisites (project_list), next steps (volume_create), and related tools (service_info, database_deploy). This gives comprehensive context about when and why to use this tool.

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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