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reaper_analyze_project

Idempotent

Renders the project master mix, measures loudness and balance metrics, then optionally sends audio and measurements to Gemini for grounded feedback.

Instructions

One-call mix check: quick-export the master mix, then analyze it.

This is the convenient path — no need to pre-configure the render dialog or pass a file. It tells Reaper to render the master mix to a temp file (reusing your project's render codec, e.g. WAV), measures it with local DSP (LUFS, peak, crest, per-band balance, stereo width), then — unless include_ai=false — uploads a small compressed proxy plus those measurements to Gemini for grounded feedback.

Requires the optional deps (pip install -e .[analyze]) and GEMINI_API_KEY for the AI layer. For best results set the project's render source to 'Master mix' and format to a single audio file. Writes a temp render but does not modify the project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focusNoOptional free-text note on what to focus on, passed to Gemini (e.g. 'the vocal sounds buried', 'too boomy on small speakers').
reference_pathNoOptional path to a reference/commercial track to compare against.
boundsNoRender the whole 'project' or just the current 'time_selection'.project
include_aiNoIf true, send a small audio proxy + metrics to Gemini for written feedback. If false, return only the measured DSP metrics (no API call).
modelNoGemini model that listens to the mix: 'gemini-2.5-flash' (fast/cheap) or 'gemini-2.5-pro' (deeper analysis).gemini-2.5-flash
response_formatNo'markdown' for human-readable output or 'json' for machine-readablemarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description discloses key behavioral traits: it renders to a temp file (reusing project's render codec), measures local DSP (LUFS, peak, crest, per-band balance, stereo width), and optionally uploads a small proxy to Gemini. It explicitly states 'Writes a temp render but does not modify the project,' which adds crucial context beyond annotations (idempotentHint=true). It also mentions dependencies and key requirements.

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?

The description is well-structured in three short paragraphs. The first sentence is a clear summary. It front-loads the purpose and then covers prerequisites, behavioral details, and parameter implications. Every sentence adds value without redundancy.

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

Completeness5/5

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

Given the tool's complexity (6 parameters, with output schema, and integration with rendering and AI), the description covers the full workflow: what happens, what is required, what the user can expect. It explains the optional AI layer and the fallback. The output schema exists, so return values do not need to be detailed in the description.

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?

Schema coverage is 100%, so each parameter is described. The description adds context: 'focus' is a free-text note passed to Gemini, 'include_ai' controls whether upload happens, 'bounds' for render span, etc. It also explains the effect of include_ai=false (only DSP metrics, no API call). This enhances understanding beyond the schema alone.

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 it is a 'One-call mix check: quick-export the master mix, then analyze it.' This distinguishes it from siblings like reaper_render_project (which likely only renders) and reaper_analyze_mix (which probably analyzes an existing mix). It specifies the verb 'analyze' and resource 'project' with the action of rendering first.

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 frames this as the 'convenient path' without needing to pre-configure the render dialog, implying it simplifies the workflow. It also gives prerequisites: setting project's render source to 'Master mix', format to single audio file, and requiring optional deps and GEMINI_API_KEY for AI. It does not explicitly state when not to use or name alternatives, but the sibling list provides context for differentiation.

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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