Final Cut Pro MCP Server

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

No annotations are provided, so the description carries full burden. It mentions 'AI-powered' and 'neural network-based tracking,' hinting at computational intensity, but lacks details on permissions, side effects (e.g., whether it modifies media), performance characteristics, or error handling. For a tool with AI components, this is a significant gap in behavioral disclosure.

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 concise with two sentences that directly address the tool's function. It's front-loaded with the core purpose and avoids unnecessary fluff. However, the second sentence slightly repeats the first ('tracking' is mentioned twice), preventing a perfect score.

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 no annotations, no output schema, and a single parameter with full schema coverage, the description is minimally adequate. It covers the high-level purpose but lacks details on behavioral traits, usage context, or output expectations. For an AI-powered tool in a complex editing environment, this leaves gaps in helping the agent understand its role fully.

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?

Schema description coverage is 100%, with the action parameter's enum values well-documented in the schema. The description adds no additional parameter semantics beyond implying general tracking/segmentation context. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't compensate with extra insights like default behaviors or inter-parameter dependencies.

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 clearly states the tool's purpose: 'AI-powered object tracking and segmentation mask controls' and 'Uses neural network-based tracking to follow objects across frames.' It specifies the verb (tracking/segmentation controls) and resource (objects across frames), but doesn't explicitly differentiate from sibling tools like 'add_mask' or 'clip_appearance' that might involve similar visual manipulation.

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?

No guidance is provided on when to use this tool versus alternatives. The description mentions tracking and segmentation controls but doesn't specify scenarios, prerequisites, or exclusions. With many sibling tools for visual editing (e.g., 'add_mask', 'color_correction_nav'), the lack of usage context leaves the agent to guess based on the action parameter alone.

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