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remix_plex_track

Search Plex for a track, extract stems, create an AI remix via Suno, and load it to a VirtualDJ deck for live mixing.

Instructions

Take a track from Plex library and create an AI remix.

Workflow:

  1. Search Plex for the track

  2. Extract stems (vocals, instruments, bass, drums)

  3. Send stems + style to Suno for reimagining

  4. Generate new remix

  5. Load to VirtualDJ deck

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deck_idNoDeck to load remix to
plex_searchYesSearch query for Plex library
remix_styleYesStyle for the remix Example: "drum and bass", "lo-fi", "orchestral"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does disclose meaningful behavior: a multi-stage pipeline with an external AI service (Suno), intermediate stem extraction, and a side effect on live state ('Load to VirtualDJ deck'). It omits latency/expected duration, failure and partial-completion behavior (e.g. if Suno fails after stems are extracted), and whether the target deck is overwritten.

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

Conciseness4/5

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

Front-loaded with a one-line purpose followed by a tight five-step numbered workflow; each line carries distinct information and nothing is redundant. It is slightly longer than strictly necessary for a three-parameter tool, but the size is justified by the multi-stage chain.

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

Completeness4/5

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

An output schema exists, so return values need no explanation, and the description covers the operational sequence an agent needs to decide to call it. It could be more complete about preconditions (required services/deck state) and the consequences of the final load step, given this is an unannotated tool with a live-state side effect.

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?

Schema coverage is 100% (all three parameters are documented in the schema, including the deck_id default and a style example), so the baseline is 3. The description only loosely reinforces the parameters by referencing search (step 1), style (step 3), and deck (step 5), adding no syntax, format, or constraint detail beyond the schema.

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

Purpose4/5

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

States a specific verb and resource ('Take a track from Plex library and create an AI remix') and concretely enumerates the pipeline (Plex search → stem extraction → Suno → remix → VirtualDJ deck). The purpose is unambiguous, but it never distinguishes itself from plausible siblings such as ai_mashup or songgen_to_deck, which an agent could easily confuse with this one.

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?

Usage is implied by the workflow itself: an agent can infer this is the tool for 'remix an existing Plex track into a new style on a deck'. However there is no explicit when-to-use/when-not, no statement of prerequisites (Plex configured, Suno reachable, VirtualDJ running), and no routing away from the many similar AI production siblings.

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