Reel-E

Read the song's structure

read_music_structure

Read-onlyIdempotent

The playing track's structure laid against the video's cuts: BPM and bar length, the sections (intro, verse, chorus, bridge, outro and so on) with song and video times and loudness, the drop (where the full sound returns), separately when the beat comes in, the part of the song the video plays, and every shot with its start, its length in bars, the bar its cut lands on and which transitions its gap allows. Read it before a music-aware request such as transitions on the beat or at the drop, faster paced or ending on the last chorus. Only name drop or section times read here. For more interesting transitions, a speed ramp or dissolve (set_transition) on one or two cuts at section changes or the drop is usually enough; AI Seamless needs request_ai_seamless and the person's yes.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "listingId": "<listingId>"
    },
    "name": "read_music_structure"
  }
}

Input Schema

Name	Required	Description	Default
`listingId`	Yes	Listing id from list_listings.

Output Schema

Name	Required	Description	Default
`status`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 9, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive behavior, and the description goes further by scoping what may be asserted from the response ('Only name drop or section times read here') and by disclosing that AI Seamless is a separate consent-gated operation. The one weak line is that 'Only name drop or section times read here' is ambiguously worded, so the constraint's intent is inferable but not crisp.

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

Conciseness3/5

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

The core return inventory is front-loaded, which is right, but it is delivered as one very long comma-chained sentence with hedges like 'and so on'. The trailing guidance about set_transition and AI Seamless is useful yet packed into a single run-on clause that dilutes the reading.

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?

With an output schema present, return values needn't be described, yet the description still tells the agent what it will learn, and it adds the follow-up path and consent prerequisite. What's missing is only a crisp statement of the constraint on reusing the data, which the ambiguous 'only name...' sentence gestures at rather than states.

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% and the single listingId parameter is documented there as coming from list_listings, so the description adds nothing about parameters. Per the high-coverage baseline, a 3 is appropriate.

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 names a specific resource (the playing track's musical structure aligned to the video's cuts) and enumerates the concrete contents: BPM, bar length, sections with song/video times and loudness, drop, beat entry, used portion, and per-shot cut data. That level of detail makes it unmistakable against siblings like set_transition or list_music.

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

Usage Guidelines5/5

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

It states explicitly when to read it ('before a music-aware request such as transitions on the beat or at the drop, faster paced or ending on the last chorus') and routes elsewhere for the follow-up action, naming set_transition and request_ai_seamless. It even flags that AI Seamless additionally requires a separate request plus the person's consent, which is a real exclusion/prerequisite.

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

All Reel-E tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?