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Glama

get_transcription

Retrieve the status or final transcript of an Orchard transcription job using its job ID, with optional formatting as JSON, text, Markdown, SRT, or VTT.

Instructions

Fetch the status or final transcript of a previously started Orchard transcription job (use the job_id returned by the transcribe tools). Optionally return it formatted as srt, vtt, md or plain text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNojson
job_idYesJob id returned by a transcribe tool.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description must convey behavioral traits. It discloses that it returns status or final transcript and supports formatting options, implying a read operation. However, it does not explicitly state that it is non-destructive, nor does it mention error behavior (e.g., job not found) or rate limits. This is a moderate gap for a tool with zero annotation coverage.

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?

The description is a single, well-structured sentence that front-loads the core action ('Fetch the status or final transcript') and immediately follows with the required job_id context and optional formatting options. There is no wasted text; every clause adds value.

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?

The tool is a simple retrieval operation with no output schema and no annotations. The description covers the essential usage (job_id requirement), the return type (status or transcript), and formatting options. It does not detail the structure of the status object or error conditions, but these are minor for an agent that only needs to call it correctly. Overall, it is sufficiently complete for its simplicity.

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 50% (job_id has a description, format has only an enum). The description adds meaning to the format parameter by listing 'srt, vtt, md or plain text', which clarifies the enum values. For job_id, it merely restates the schema's description, so it does not add extra semantics. It partially compensates for the missing format description but does not fully explain all parameters.

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 clearly states the verb 'Fetch' and the resource 'transcription job', and specifies it retrieves status or final transcript for previously started jobs. It distinguishes itself from siblings like transcribe_file and transcribe_url (which start jobs) and get_usage (which reports usage), making the purpose unambiguous.

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 provides clear context by instructing to use the job_id returned by transcribe tools, establishing a prerequisite. It does not explicitly mention when not to use it or list alternatives, but the sibling names imply the distinction. It lacks explicit exclusions but is clear enough for an agent to decide when to call it.

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