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Glama

sfx_presets

List gen_sfx presets and all overridable override fields with defaults to prevent failures from misspelled or guessed parameter names.

Instructions

列出 gen_sfx 能用的 preset, 以及 overrides 里可以覆盖的全部字段和它们的默认值。

先看这里再去 overrides: 字段名写错了 gen_sfx 会直接失败, 而"有哪些字段"是猜不出来的 (占空比扫描叫 duty_sweep 还是 duty_slide, 低通叫 lpf 还是 cutoff)。

返回: preset 名单 + 参数默认值表 + 采样率。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
rateNo
errorNo
paramsNo
presetsNo
warningsNo
error_codeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.5

TDQS

A4.7/5.0
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 useful traits: exact field-name sensitivity that causes hard failure in gen_sfx, the fact that valid field names cannot be inferred, and the shape of the return (preset list, defaults table, sample rate). It is a read-only listing so auth/rate-limit disclosure is not critical, but no explicit statement of read-only safety is given.

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?

Front-loads the purpose, then the reason to use it, then the return contents. The parenthetical naming examples look verbose but each one illustrates a real ambiguity risk, so every sentence earns its place.

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 zero-parameter discovery tool with an output schema present, the definition is complete: it explains what to consult it for, why it matters, and sums up the return contents. Nothing an agent needs to call it or act on the result is missing.

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?

Zero input parameters, so the baseline is 4. The description additionally explains what the returned field table means and gives examples of ambiguous field names (duty_sweep vs duty_slide, lpf vs cutoff), adding interpretive value beyond the empty schema.

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?

States a specific verb (list) and resource (presets usable by gen_sfx), and goes further by naming the overrides fields and their defaults as part of the payload. It is clearly distinguishable from the sibling gen_sfx: this is the discovery/companion tool the agent consults before invoking gen_sfx.

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

Usage Guidelines5/5

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

Gives explicit routing ('先看这里再去 overrides' – look here before touching overrides) tied to a concrete failure mode (wrong field names make gen_sfx fail). It identifies the sibling gen_sfx as the downstream consumer and the reason guessing field names is unsafe.

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