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mcp_opendaw_render_and_analyze

Render your current project and analyze the mix in one action—receiving LUFS, spectrum, stereo, dynamics, and prioritized suggestions to guide your next mix adjustments.

Instructions

Render the current project and run full audio analysis in one call.

Combines export_audio + analyze_mix into a single tool — the feedback loop for iterative mixing. Agent renders, listens, and gets concrete numbers: LUFS, spectrum, stereo, dynamics, and prioritized suggestions.

This is the 'ears' tool. After making mix changes, call this to verify:

  1. Renders project to WAV via offline engine

  2. Runs full mix analysis (LUFS, spectrum, stereo, dynamics)

  3. Returns concrete numbers + prioritized suggestions

filename: Output filename (without .wav extension). sample_rate: Render sample rate (48000 recommended). analysis_depth: "full" (all analyses) or "quick" (LUFS + spectrum only).

Returns analysis JSON with mix_suggestions, master_check, and file path.

Example:

After adjusting mix

result = render_and_analyze("my_mix")

→ {lufs: -14.2, spectrum: {...}, suggestions: [...], file: "..."}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filenameNorender_analysis
sample_rateNo
analysis_depthNofull

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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 provides good insight: it renders to WAV via offline engine, runs full analysis (LUFS, spectrum, stereo, dynamics), and returns concrete numbers plus prioritized suggestions. It also explains the difference between 'full' and 'quick' analysis depth. However, it omits potential side effects like file overwrites or timing considerations.

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?

The description is well-structured with a clear opening, numbered steps, and an example. It front-loads the purpose and remains focused. There is slight redundancy ('feedback loop' and 'After making mix changes, call this to verify' overlap), preventing a perfect score.

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?

For a combined render+analyze tool, the description covers what it does, when to use it, all parameters, and the return structure (analysis JSON with mix_suggestions, master_check, file path). It could mention where the WAV file is saved or whether it overwrites existing files, but it is largely complete for agent invocation.

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 the description fully explains all three parameters: filename (output filename without .wav extension), sample_rate (48000 recommended), and analysis_depth ('full' vs 'quick' with exact meanings). This far exceeds the bare schema and makes parameter choice unambiguous.

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 verb+resource: 'Render the current project and run full audio analysis in one call.' It distinguishes itself by explicitly saying it combines export_audio + analyze_mix and positions itself as the 'ears' tool for iterative mixing, setting it apart from sibling analysis/rendering tools.

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?

The description provides clear when-to-use guidance: 'After making mix changes, call this to verify' and frames it as the feedback loop for iterative mixing. It does not explicitly state when not to use it or name alternative tools beyond mentioning it combines two others, so a 4 is appropriate.

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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