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Glama

mixx_set

Generate optimized track sequences from crates, record DJ sessions, and analyze mixes for BPM transitions and energy using AI.

Instructions

AI-assisted set sequencing and analysis.

PORTMANTEAU PATTERN: Consolidates set planning and analysis.

SUPPORTED OPERATIONS:

  • sequence: Generate an optimized track order from a crate (requires crate) Uses local Ollama (llama3.2:3b) for harmonic mixing, energy curve, and phrase-aligned transitions.

  • record: Start/stop session recording via OSC

  • analyze_set: Analyze a recorded session or mix for BPM transitions, energy, etc.

Returns: Dict with ordered track list and reasoning

Examples: mixx_set("sequence", crate="Peak Time", name="Friday Gig") mixx_set("record") mixx_set("analyze_set", name="Last Saturday", analyze_type="recording")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
crateNo
operationYes
analyze_typeNorecording
energy_curveNobuild_peak_cooldown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.4/5.0
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 disclose meaningful traits: sequence uses local Ollama (llama3.2:3b) for harmonic mixing, energy curve, and phrase-aligned transitions; record operates via OSC and can start or stop a session (a side effect). It stops short of stating OS/permission prerequisites or error/limitation behavior.

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?

Front-loaded with a one-line purpose, then well-labeled PORTMANTEAU/OPERATIONS/RETURNS/EXAMPLES sections that make the multi-op tool easy to scan. The 'Returns' block is partly redundant given an output schema exists, but overall the structure is efficient.

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?

For a portmanteau tool with 5 params, 0% schema coverage, and no annotations, the description is only partially complete: operations are well covered and returns are covered by the output schema, but undocumented parameters (energy_curve) and no alternative-routing leave gaps for correct invocation.

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

Parameters2/5

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

Schema description coverage is 0% and the description barely compensates. It clarifies that 'crate' is required for sequence and demonstrates 'name' and 'analyze_type="recording"' in examples, but it never explains 'energy_curve' (a defined parameter with default build_peak_cooldown) or the semantics/defaults of 'name' across operations.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb+resource ('AI-assisted set sequencing and analysis') and enumerates its three operations with the action each performs. It does not, however, differentiate itself from a close sibling like mixx_ai_set, leaving the agent to infer the boundary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Per-operation context exists ('sequence... requires crate', 'record: Start/stop', 'analyze_set: Analyze a recorded session') and the examples show expected call shapes. But there is no explicit when-to-use vs when-not-to-use guidance and no routing to alternatives such as mixx_analyze or mixx_ai_set.

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