Skip to main content
Glama
Benedict

TidalCycles MCP Server

by Benedict

tidal_set_layer

Add or replace a named transform, source, or control layer on a TidalCycles channel and re-evaluate it, with optional variants for autopilot switching.

Instructions

Add or replace one named layer of a channel, then re-evaluate that channel. A channel's pattern is built as: $ $ ... # # . Transforms apply in the order they were added, outermost first. Each channel has one source; setting a new one replaces the old. Give variants to let tidal_autopilot switch between them. Call tidal_palette for idioms that work.

Input Schema

NameRequiredDescriptionDefault
codeYesThe layer's code, without the $ or # that joins it
kindYestransform: a function applied with $ (e.g. "every 3 (jux rev)"). source: the base pattern (e.g. 's "bd*2 sd"'). control: an effect applied with # (e.g. "crush 4").
nameYesLayer name, e.g. "rhythm", "stereo", "filter". Reusing a name replaces that layer.
channelYesThe channel (d1-d9)
variantsNoOptional alternatives the autopilot may switch to. Keep them the same shape as code.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.0

TDQS

A4.3/5.0
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 does well: it discloses add-or-replace semantics, that each channel has one source and a new one replaces the old, transform ordering ('outermost first'), and the re-evaluation side effect. It omits failure behavior and permissions, but the mutation semantics are unusually well surfaced.

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 core action is front-loaded and no sentence is pure filler; the pattern-grammar sentence and sibling pointers each earn their place. It is dense, but the density is justified by the tool's complexity.

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 5-param mutation tool with no annotations and no output schema, the description covers action, side effects, composition rules, and sibling routing. It leaves the response/return behavior and error cases unstated, which keeps it from the top score.

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 baseline is 3, but the description adds real meaning beyond the schema: it explains the pattern grammar that code slots into, clarifies transform ordering, and reinforces why variants exist. That is genuine value over the field-level docs.

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+resource ('Add or replace one named layer of a channel') plus a concrete side effect ('then re-evaluate that channel'). This clearly separates it from siblings like tidal_remove_layer, tidal_set_control, and tidal_palette.

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 guidance on using variants ('Give variants to let tidal_autopilot switch between them') and points to a sibling for valid idioms ('Call tidal_palette for idioms that work'). It stops short of explicit when-not/exclusion rules, so it lands below the top tier.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.