Skip to main content
Glama

list_transcription_presets

Lists available transcription presets by category—style or format—with optional name filter, helping you select the appropriate template for your audio transcript.

Instructions

Lists available transcription presets from the Text-Transformation-Prompt-Library. Each preset is categorized as either a "style" (modifies tone/voice without changing structure) or a "format" (restructures content into a specific document type). Use these with the transcribe_with_preset tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNoOptional text filter to search preset names (e.g. "email", "blog", "meeting")
categoryNoFilter by category: "style" for tone/voice presets, "format" for document structure presets. Omit for all.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.1

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It signals a read-only listing action through 'Lists available' and adds useful category semantics, but it does not explicitly confirm that no side effects occur or describe the shape of the returned preset entries.

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?

Two sentences, with the core action front-loaded, followed by the category distinction and downstream usage guidance. Every sentence earns its place with no filler or 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 simple list tool with two optional parameters and no output schema, the description provides the essential context: what is listed, how presets are categorized, and how they are used with transcribe_with_preset. Explicit return-field details would be a nice addition, but the tool's straightforward nature makes the description sufficient.

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?

The schema already documents both parameters at 100% coverage, but the description adds richer meaning for the enum values: 'style' modifies tone/voice without changing structure, while 'format' restructures content into a specific document type. This goes beyond the schema's brief enum comments, though it adds no detail about the filter parameter's syntax.

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 opens with a specific verb ('Lists') and a defined resource ('available transcription presets from the Text-Transformation-Prompt-Library'), then clarifies the two preset categories. This clearly differentiates it from the transcribe_* sibling tools, which perform audio transcription rather than preset listing.

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 explicitly tells the agent to use the listed presets with the transcribe_with_preset tool, establishing the expected workflow. It does not enumerate when-not-to-use or compare against each transcribe_* sibling, but the list-vs-transcribe distinction is clear from the tool names.

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