Skip to main content
Glama
norton77930

Podcast Ingestion Core MCP Server

by norton77930

transcribe_episode

Transcribe podcast episodes into text by downloading audio, with configurable model, device, and VAD filter. Requires confirm=true to execute the long-running transcription.

Instructions

Long-running side-effect tool:需要 confirm=true 才會下載/取得音檔並轉錄。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
forceNo
modelNotiny
deviceNocpu
confirmNo
podcast_idNogooaye
vad_filterNo
episode_refNolatest
compute_typeNoint8

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations present, the description carries the behavioral burden and does well by flagging long-running execution, side effects, and the confirm=true gate before any work happens. It could add more detail about what the side effects affect, but the core safety-relevant behavior is disclosed.

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?

One dense sentence with the most important facts—long-running, side-effect, and the confirmation requirement—placed right at the start. There is no redundant or filler text.

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 an 8-parameter, side-effectful, long-running tool with no annotations, this description is too thin. It explains the confirmation gate and the core operation but omits guidance on the many optional parameters and does not clarify what makes this transcribe tool distinct from nearby sibling tools.

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%, so the description must compensate, but only confirm is explained. Parameters like force, vad_filter, model, device, compute_type, and episode_ref have defaults but no intended meaning or interaction, leaving an agent to guess.

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 states a concrete action ('transcribe') and resource ('episode'), and adds that it downloads/obtains audio before transcribing. It does not explicitly contrast itself with sibling tools like download_audio or the summarization tools, so it misses the top score for sibling differentiation.

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?

It gives clear usage context: the tool is long-running and side-effectful, and must be invoked with confirm=true. However, it does not state when not to use it or name an alternative, so it stops short of full usage guidance.

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