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leancoderkavy

Premiere Pro MCP Server

add_tracks

Adds specified numbers of video, stereo, 5.1, and mono audio tracks to the active sequence, then verifies the exact requested counts were added.

Instructions

Add video and/or audio tracks through QE and verify the active sequence gained the exact requested counts

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audio_tracksNoNumber of standard stereo audio tracks to add (default: 0)
video_tracksNoNumber of video tracks to add (default: 0)
audio_51_tracksNoNumber of 5.1 audio tracks to add (default: 0)
audio_mono_tracksNoNumber of mono audio tracks to add (default: 0)
Behavior3/5

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

With annotations all set to false, the description carries the burden of behavioral disclosure. It does add transparency by stating that the tool modifies the active sequence and performs verification of exact counts. However, it does not explain what happens on verification failure, what 'through QE' entails, or any side effects beyond adding tracks. This is moderate but not thorough.

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

Conciseness5/5

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

The description is a single sentence of 17 words that front-loads the primary action ('Add video and/or audio tracks'), then specifies the method ('through QE'), and the expected outcome ('verify the active sequence gained the exact requested counts'). Every word earns its place; it is concise and well-structured.

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

Completeness3/5

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

The tool is relatively simple with four fully described parameters and no output schema. The description covers the core function and verification but leaves gaps: it does not explain what QE refers to, what happens if verification fails, or clarify when to use this tool versus 'add_track'. Given the tool's simplicity, the description is adequate but not complete enough for nuanced decision-making.

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

Parameters3/5

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

The input schema already provides descriptions for all four parameters (audio_tracks, video_tracks, audio_51_tracks, audio_mono_tracks) with 100% coverage. The description repeats the concept of adding video/audio tracks but does not add any new parameter-level meaning or clarify parameter interactions. A baseline of 3 is appropriate given the high schema coverage.

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's function: adding video and/or audio tracks and verifying the active sequence's track counts. The verb 'Add' is specific, and the resource (tracks) is clear. It also distinguishes itself from the sibling 'add_track' by mentioning verification and plural tracks, making its purpose unambiguous.

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

Usage Guidelines3/5

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

The description implies usage for adding tracks and verifying counts, but it provides no explicit alternatives or when-not-to-use guidance. Sibling tools like 'add_track' exist, yet the description does not clarify when one should be preferred over the other. This leaves the decision context ambiguous.

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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