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List Lium templates

list_templates
Read-only

Docker templates a pod can start from (official ones and your own), for rent_pod template_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchNoFilter by name or image, e.g. pytorch, vllm

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful scope context (official templates plus your own) but says nothing about return format, ordering, or pagination for what could be a large list. With annotations carrying safety, a 3 is appropriate.

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?

A single compact sentence with the resource front-loaded and zero filler. The trailing 'for rent_pod template_id' is telegraphic but purposeful, earning its place by linking to the workflow.

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 simple read-only list tool with one fully documented optional parameter and no output schema, the description covers what the resource is and why it exists. Only minor gaps remain (no mention of the search filter or result size), which is acceptable at this complexity.

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?

Schema description coverage is 100% — the single 'search' parameter is fully documented in the schema with examples (pytorch, vllm). The description does not mention the search/filter capability at all, so it adds no meaning beyond the schema. Baseline 3 applies when the schema does the work.

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 names a specific resource ('Docker templates a pod can start from') and clarifies the scope by noting both official and user-owned templates. It also ties the resource to a concrete downstream use (rent_pod template_id), which helps an agent place it. It doesn't explicitly differentiate from siblings like search_gpus or search, but the resource noun is unique enough.

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

Usage Guidelines3/5

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

The phrase 'for rent_pod template_id' implies the intended workflow: call this to obtain a template_id before renting a pod. However, there is no explicit when-to-use/when-not guidance and no named alternative, so the usage is only implied rather than stated.

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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