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Create automation lane

create_automation_lane

Build an automation lane that records a target parameter’s live sweep into a circular buffer and loops it back on a bar-phase clock for synchronized parameter modulation.

Instructions

Build a per-parameter automation lane that records a live parameter sweep into a circular buffer over N bars, then loops the recording back into the parameter on a bar-phase clock. Two modes: record (sample the target param every cook into a ring buffer) or loop (read the buffer back via Lookup CHOP bound to the target param). Re-calling with the same name and a different mode flips the state without rebuilding the network. Uses Beat CHOP → Select CHOP (rampbar) → Lookup CHOP playback, with COMP storage tracking mode/write_head/armed state. Returns a summary plus a JSON block with container path, mode, samples count, target, and any warnings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bpmNo
barsNo
modeNorecord
nameYesSystem container name, e.g. 'auto_lane_filter'
parentNoParent COMP path, defaults to '/'
targetParamYesOP path + param tuple, e.g. '/project1/filter1:cutoff'
Behavior4/5

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

The description discloses key runtime behaviors beyond the annotations: the two modes, the internal CHOP chain (Beat→Select→Lookup), the fact that re-calling with the same name and different mode flips state without rebuilding, and the return of a summary and JSON block. This complements the annotations (readOnlyHint=false, destructiveHint=false, openWorldHint=true) with actionable details.

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 dense but every sentence contributes: purpose, modes, re-call semantics, implementation details, and return format. It packs substantial information without redundancy.

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 6-parameter tool with no output schema, the description covers the workflow, modes, return structure, and state management. It does not list per-parameter details for bpm/parent, but these are self-explanatory and not critical to the tool's core function.

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?

The schema has 50% description coverage, and the description adds conceptual meaning to key parameters: it explains 'record' and 'loop' modes (matching the mode enum) and 'N bars' for the bars parameter. However, it does not elaborate on bpm or parent, which are left to their self-explanatory names and schema defaults.

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 uses the specific verb 'Build' and defines a concrete resource: 'a per-parameter automation lane that records... into a circular buffer over N bars, then loops...'. It clearly differentiates from siblings by focusing on the automation lane concept and its two modes.

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 explains when the tool is appropriate by detailing the record/loop modes and the state-flip behavior on re-invocation, giving clear context for usage. It does not explicitly name alternative tools or state when not to use it, but the context is sufficient for an agent to match the tool to the task.

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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