KlingMCP

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

With no annotations provided, the description carries the full burden. It discloses the async pattern (returns Task ID and state), explains the interpolation behavior ('smooth motion between them'), and states the critical constraint that at least one image URL is required. However, it omits operational details like cost/quota implications, privacy considerations of sending image URLs, or error handling patterns expected for a 12-parameter AI generation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections: purpose, mechanism, usage scenarios, constraints, and returns. It is front-loaded with the core function. The 'Returns' section is slightly redundant given the output schema exists, but it clarifies the Task ID async pattern which may not be immediately obvious from schema structure alone.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the rich input schema (100% coverage, 12 parameters with enums) and presence of an output schema, the description appropriately focuses on high-value additions: differentiating purpose, usage scenarios, and cross-parameter validation constraints. It does not need to enumerate individual parameters or return fields, and successfully covers the essential domain-specific logic for an image-conditioned video generation tool.

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

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

While the input schema has 100% description coverage (baseline 3), the description adds crucial semantic constraints not captured in the schema: specifically, that 'At least one of start_image_url or end_image_url must be provided' despite both being optional in the schema with default values. It also clarifies how the parameters interact ('animate from this image... towards this image').

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

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

The description explicitly states the tool 'Generate[s] AI video using reference images as start and/or end frames', using a specific verb and resource combination. It clearly distinguishes this from siblings like kling_generate_video (text-to-video) and kling_extend_video by emphasizing the image reference capability and 'smooth motion between' frames functionality.

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

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

The description includes an explicit 'Use this when:' section with three specific scenarios (animating specific images, creating transitions between two images, precise visual control). While it effectively implies when to use this over alternatives, it lacks explicit 'when not to use' guidance or named sibling alternatives (e.g., 'don't use for text-only generation').

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.