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Glama

panopto_transcript

Fetches timestamped transcripts from Panopto lecture recordings by course and recording ID, transcribing audio when no captions exist and caching results.

Instructions

Panopto ders kaydının zaman damgalı konuşma metni ("[12:34] ..."). Altyazı yoksa ses yazıya çevrilir: uzun kayıtta dakikalar sürebilir; sonuç önbelleğe yazılır, ikinci istek anında döner.

Input Schema

NameRequiredDescriptionDefault
idYespanopto_videos'tan kayıt kimliği
courseYesDers kodu
offsetNoUzun metinde başlangıç karakteri (varsayılan 0)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
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 substantial work: it discloses the return format, that audio is transcribed via ASR when no captions exist, that long recordings can take minutes, and that results are cached so repeat requests are instant. Missing only error behavior and what happens when transcription fails or the recording has no audio.

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 dense sentences, with the purpose front-loaded and the second sentence packing fallback behavior, latency, and caching without a wasted word. Structure is efficient and easy to scan.

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 three-parameter read tool with no output schema, the description conveys the return shape, the cost/latency profile, and caching, which is most of what an agent needs to decide to call it. The notable gap is pagination: the presence of 'offset' suggests truncated transcripts, but the description never says so.

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 100%, so all three parameters are already documented, which sets the baseline at 3. The description adds the output format example and implies that long transcripts may need to be walked through, but never explains the 'offset' parameter or when a transcript would be truncated.

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 names a specific resource (the timestamped transcript of a Panopto lecture recording) and even shows the output shape with '[12:34] ...'. It is clearly distinct from panopto_videos, which supplies the 'id', but the description itself never names that sibling, so the differentiation comes from the schema rather than the text.

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?

The implied use case (fetch the spoken content of a recorded lecture) is clear, and the fallback note about missing subtitles is useful context. However, there is no explicit when-to-use / when-not-to-use guidance and no pointer to panopto_videos as the place to obtain the record id.

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