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mcp_opendaw_render_full_song

Automatically detect song length from all note and audio regions, then render the full project to WAV with a configurable tail for reverb/delay tails.

Instructions

Render the entire project — auto-detects song length from all regions.

Scans all note and audio regions across all tracks to find the latest ending point, then renders from beat 0 to that point plus a configurable tail for reverb/delay tails. No manual beat counting needed.

This closes the pipeline gap: after create_song_with_variations (or any arrangement tool), call render_full_song to get the final WAV.

filename: Output filename (without .wav extension). sample_rate: Export sample rate (default 48000). tail_beats: Extra beats at the end for reverb/delay tails (default 4 = 1 bar).

Returns the path to the exported WAV, song duration in seconds, and audio metadata (peak, has_audio).

Example:

After building a song

create_song_with_variations("dnb") render_full_song(filename="my_dnb_track")

Shorter tail for tight electronic

render_full_song(filename="techno_mix", tail_beats=2)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filenameNofull_song
tail_beatsNo
sample_rateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so description must carry full burden. It explains auto-detection of song length, scanning all regions, rendering from beat 0 to end plus configurable tail. Discloses return values (path, duration, metadata). Lacks details on empty project behavior, but overall transparent.

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?

Description is well-structured: what it does, how it works, pipeline usage, parameters, and examples. Front-loaded with purpose, no superfluous sentences. Efficient and clear.

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?

Given 3 optional parameters and existence of output schema (inferred from context), description covers core functionality, usage, and return information. Does not mention error conditions or prerequisites like having a project loaded, but is still fairly complete for a render tool.

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

Parameters5/5

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

Schema description coverage is 0%, but description provides clear explanations for all three parameters: filename (without .wav), sample rate, tail_beats (purpose and default). Adds significant meaning beyond the bare schema.

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?

Description clearly states it renders the entire project, auto-detects song length by scanning all regions. Differentiates from siblings like render_range by being the full render tool. Verb 'render' + resource 'full song' is specific.

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

Usage Guidelines4/5

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

Explicitly says it closes the pipeline gap after arrangement tools like create_song_with_variations, with examples showing different tail_beats for different genres. Does not explicitly mention alternatives for partial renders, but context is sufficient.

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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