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Doseedo: Film Scoring, AI Instruments, Sound Effects & Stems

Bounce a session

doseedo_bounce_session

Bounce a session (or specific tracks) to audio through their REAL plugin chains, offline — Dø Desktop renders them in the background WITHOUT the user opening the DAW (live via Logic if it's open, headless if it isn't; this is the thing stock DAWs can't do). Headless renders AUDIO tracks only — an instrument/MIDI track needs the project open in Logic. A track that could not render is named in the error with its reason. Async: returns a job_id — poll with doseedo_wait_task. The result is downloadable stem URLs. Needs Dø Desktop to run at some point to pick up the job; until then it stays queued. No credits (rendered on the user's machine). Cancel: a bounce still queued never renders (its budget is refunded); one mid-render has its result dropped on arrival.

Input Schema

NameRequiredDescriptionDefault
stemsNotrue (default) = one file per track; false = a single mixdown.
formatNoOutput format (default wav).
track_idsNoTracks to bounce (t_… ids from doseedo_get_session). Omit to bounce the whole session.
session_idYes
tail_secondsNoExtra seconds for reverb/delay to ring out (default 2).
idempotency_keyNoOptional. Any unique string for THIS request (e.g. a UUID). Re-sending the same call with the same key after a timeout returns the same job instead of starting a second one.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

The description adds substantial behavioral context beyond the annotations: async job_id return, queued-until-desktop-picked-up state, no credits because rendering is local, named failing tracks with reasons, and detailed cancel semantics including refunds and dropped mid-render results. These are exactly the operational details an agent needs before invoking a long-running mutation.

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 dense but front-loaded: the main action and offline/real-plugin distinction come first, followed by constraints and async behavior. The long parentheticals and cancellation detail make it slightly heavier than necessary, though nearly every sentence carries useful information.

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?

For a complex async render tool with no output schema, the description covers the missing pieces: return shape (job_id, later stem URLs), polling tool, queueing dependency on Dø Desktop, track-render limitations, billing, and cancellation behavior. An agent has enough information to invoke and follow up correctly.

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 description coverage is already high at 83%, so most parameter meaning is provided structurally. The description reinforces that track_ids can target specific tracks and that results are downloadable stem URLs, but it does not explain format, tail_seconds, or idempotency_key beyond what the schema already says.

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 states a specific verb and resource ('Bounce a session (or specific tracks) to audio') and distinguishes it from generic DAW rendering by explaining that it uses real plugin chains offline. It also differentiates from siblings implicitly by noting that headless renders are audio-only and that instrument/MIDI tracks require Logic open.

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?

It gives clear usage context: offline background rendering via Dø Desktop, headless audio-only limitation, need for Dø Desktop to pick up the job, and polling with doseedo_wait_task. It does not explicitly name alternative sibling tools such as doseedo_mix or doseedo_render_midi, so it stops short of full when-to-use alternative routing.

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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