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mcp_opendaw_render_and_analyze

Render your project to WAV and get full mix analysis including LUFS, spectrum, stereo, and dynamics, with prioritized suggestions for improvement.

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
Behavior3/5

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

The description outlines the three steps (render, analyze, return) and mentions offline engine, LUFS, spectrum, stereo, dynamics, and suggestions. With no annotations, it partially transparent but lacks disclosure on file persistence, permissions, or side effects of rendering to WAV.

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 summary, numbered list, parameter section, and example. It is front-loaded and clear, though slightly repetitive (e.g., 'feedback loop' appears twice) and could be trimmed.

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?

Given the tool's complexity and lack of annotations, the description covers core functionality, parameters, and return structure. It lacks details on file location/persistence, error scenarios, and prerequisites, leaving gaps for an agent to infer.

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

Parameters4/5

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

With 0% schema coverage, the description adds meaningful explanations for all three parameters: filename extension, recommended sample rate, and analysis depth options. It does not provide constraints or enums explicitly but compensates well through descriptive text.

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 that the tool renders the project and runs full audio analysis in one call. It distinguishes itself from siblings by explicitly combining export_audio and analyze_mix, making its purpose as a feedback loop for iterative mixing unmistakable.

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 indicates the tool is the 'ears' tool for verifying mix changes, implying usage after adjustments. It mentions it combines export and analysis, hinting that standalone tools exist for separate tasks. However, it does not provide explicit when-not-to-use scenarios or enumerate alternatives.

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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