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luma_list_actions

Discover all Luma API actions and their corresponding tools. Browse this categorized reference to identify which tool handles video generation, extension, and loop creation tasks.

Instructions

List all available Luma API actions and corresponding tools.

Reference guide for what each action does and which tool to use.
Helpful for understanding the full capabilities of the Luma MCP.

Returns:
    Categorized list of all actions and their corresponding tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the return value ('Categorized list of all actions'), which adds value. However, it omits other behavioral traits like whether this is a cached operation, rate limits, or authentication requirements that annotations would typically cover.

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 efficiently structured with four sentences: purpose declaration, usage context, value proposition, and return specification. Each sentence earns its place without redundancy or filler text.

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 the tool has an output schema (per context signals) and zero parameters, the description provides appropriate completeness by summarizing the return structure. It acknowledges the ecosystem of sibling tools by explaining this maps actions to tools, though it could explicitly mention it complements the specific action tools listed.

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 input schema contains zero parameters. According to scoring rules, 0 parameters establishes a baseline score of 4. The description correctly does not invent parameters where none exist.

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 uses specific verb 'List' with clear resource 'Luma API actions and corresponding tools'. It effectively distinguishes itself from sibling execution tools (generate_video, extend_video, etc.) by positioning itself as a discovery/meta-tool that catalogs available capabilities.

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 states it is a 'Reference guide for what each action does and which tool to use' and is 'Helpful for understanding the full capabilities'. This implies usage context (when unsure which tool to use), though it could be more explicit about using this before attempting operations with sibling tools.

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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