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kling_list_actions

Explore available Kling AI video generation actions and matching tools. Browse categorized API capabilities to find the right function for text-to-video, image-to-video, and quality model workflows.

Instructions

List all available Kling 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 Kling 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adequately describes the return value ('Categorized list') but omits safety indicators (read-only nature), API interaction details (whether this requires auth or hits live API vs. cached data), and error conditions. The 'List' verb implies read-only behavior, but explicit confirmation is absent.

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?

The description is appropriately front-loaded with the core action ('List all available...') in the first sentence. Four sentences total with minimal redundancy (sentences 2 and 3 overlap slightly in explaining the reference nature). The 'Returns:' section is structured and clear.

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 this is a simple discovery tool with zero input parameters and an existing output schema, the description provides sufficient context. It explains the tool's meta-purpose adequately, though it could explicitly state this is safe to call without side effects given the lack of readOnlyHint annotations.

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?

Input schema contains zero parameters. According to the evaluation rubric, 0 params equals a baseline score of 4. No parameter documentation is required or expected.

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 'List[s] all available Kling API actions and corresponding tools' using a specific verb and resource. It distinguishes itself from sibling execution tools (generate_video, extend_video, etc.) by positioning this as a 'Reference guide' for capability discovery rather than an action tool.

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 implies usage context by stating it helps understand 'which tool to use' and is 'Helpful for understanding the full capabilities,' suggesting when to reach for this vs. direct execution. However, it lacks explicit when-not guidance or clear statements like 'Use this first when uncertain which generation tool to invoke.'

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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