LumaMCP

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

With no annotations provided, the description carries the full burden. It successfully discloses the return format ('Table of all aspect ratios with their descriptions and use cases') and the fact that it includes use case guidance, not just raw values. Lacks details on caching, rate limits, or failure modes, but covers the essential behavioral trait (what it returns) for a read-only enumeration 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?

Four sentences that each serve distinct purposes: purpose statement, behavioral description, usage guideline, and return value specification. Minor redundancy exists between sentence 2 ('Shows... use cases') and sentence 4 ('Returns: Table... use cases'), but overall efficiently structured and front-loaded with the core verb.

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?

For a simple zero-parameter discovery tool with an output schema present, the description is complete. It explains what data the table contains (descriptions and use cases) and contextualizes it within the video generation workflow without needing to specify implementation details.

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?

Input schema has 0 parameters, establishing a baseline of 4. The description correctly implies no inputs are needed by stating it lists 'all' available ratios without qualifying required filters or identifiers.

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 opens with a clear verb ('List') and specific resource ('aspect ratios for Luma video generation'). It clearly distinguishes from sibling tools like luma_generate_video or luma_extend_video by identifying this as a metadata discovery tool rather than an action or mutation tool.

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?

Explicitly states when to use: 'Use this to understand which aspect ratio to choose for your video.' This provides clear context for the tool's role in the workflow. Could be improved by explicitly referencing the sibling generation tools (e.g., 'use before calling luma_generate_video'), but the guidance is clear without being misleading.

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