LumaMCP

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

No annotations are provided, so the description carries full disclosure burden. It successfully documents the task state lifecycle (pending/completed/failed) and summarizes return values (URLs, dimensions, thumbnail). It could improve by mentioning polling patterns or error handling specifics, but the state machine documentation is excellent.

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?

Well-structured with clear sections (purpose, usage scenarios, states, returns). The opening sentence immediately conveys core functionality. Minor redundancy exists between the opening line ('retrieve the resulting video URLs') and the Returns section, but overall information density is high with no extraneous content.

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 single-parameter status-checking tool with an output schema, the description is complete. It provides essential domain-specific context (the task state definitions) that structured fields cannot convey, ensuring the agent understands the polling lifecycle. No critical gaps remain given the tool's simplicity.

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?

With 100% schema coverage, the baseline is 3. The description adds workflow context by repeatedly referencing 'previous generation' and 'generation request,' which semantically links the task_id parameter to the output of sibling tools (luma_generate_*, luma_extend_*), adding valuable usage context beyond the schema's technical description.

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 specific verb ('Query') and clearly identifies the resource (video generation task status and result). It explicitly distinguishes this tool from its siblings (luma_generate_*, luma_extend_*) by positioning it as the status checker/retrieval mechanism rather than the creation mechanism.

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?

Contains an explicit 'Use this when:' section with three specific scenarios (checking completion, retrieving URLs, getting full details). This provides clear guidance on when to select this tool over generation alternatives and implies the prerequisite of having initiated a generation first.

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