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Glama

create_ambient_soundscape

Generates an evolving ambient soundscape by layering a drone with slowly swelling tones. Set mood, density, pitch range, duration and effects to shape a reproducible audio piece.

Instructions

Play an evolving ambient piece: a drone with slowly swelling, overlapping tones.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "create_ambient_soundscape"
  }
}

Input Schema

NameRequiredDescriptionDefault
moodNocalm
seedNoRandom seed for a reproducible result; omit for a new one
volumeNoLoudness, 0..1
densityNoHow many sound events overlap
effectsNoOverride the mood's own reverb/delay
durationNoSeconds
pitch_rangeNomedium

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare destructiveHint=false, openWorldHint=false and non-idempotent behavior, so the agent knows it is a safe, non-repeating generation. The description adds useful sonic character ('slowly swelling, overlapping tones') that helps predict output, but says nothing about real-time playback behavior, whether the call blocks for the duration, or how output is returned.

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?

A single front-loaded sentence with no filler; the evocative wording earns its place by conveying the musical character. It is efficient, though it comes at the cost of any practical usage detail.

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

Completeness2/5

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

For a seven-parameter generative audio tool with mood presets, effects override, pitch range and density, one sentence is thin. The output schema relieves the need to explain return values, but the complete absence of when-to-use context or sibling differentiation leaves the agent under-informed.

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 coverage is 71% with descriptive text on volume, density, duration, seed and the nested effects object, so the schema does most of the work. The description mentions none of the parameters and adds no meaning beyond what the schema already documents, making baseline 3 appropriate.

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?

States a specific verb ('Play') and a specific resource ('an evolving ambient piece: a drone with slowly swelling, overlapping tones'), so the agent knows this produces ambient drone audio. It implicitly distinguishes itself from siblings like play_synth or create_granular_texture by describing the sonic result, but never names those alternatives.

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

Usage Guidelines2/5

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

There is no guidance on when to choose this over the dozen sibling audio tools (play_melody, create_sequence, create_granular_texture, etc.), no prerequisites, and no exclusion criteria. The agent must infer the use case entirely from the one-line sonic description.

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