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spraay_compute_stt

Transcribe audio from a URL using Whisper. Costs $0.02 USDC per request.

Instructions

Speech-to-text via Spraay Compute. Transcribe audio from a URL using Whisper. Costs $0.02 USDC.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoSTT model (default 'auto' = Whisper)auto
languageNoOptional language hint (e.g. 'en', 'es', 'fr')
audio_urlYesURL of the audio file to transcribe (MP3, WAV, M4A, etc.)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesTrue when the gateway call succeeded; false when it returned an error.
dataNoThe gateway response payload on success. The exact shape depends on the tool (see the tool description and the JSON in the text content block).
errorNoHuman-readable error message, present only when ok is false.
Behavior4/5

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

The description adds transparency by disclosing the cost of $0.02 USDC, which is a behavioral trait beyond the annotations. However, it does not discuss potential side effects like authentication requirements or data storage.

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 extremely concise with two sentences, front-loading the purpose and cost. Every word adds value with no 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 straightforward speech-to-text tool with an output schema, the description covers the core functionality and cost. Some details like file size limits or supported languages are omitted, but overall it is sufficiently complete.

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?

The input schema has 100% description coverage, and the tool's description adds minimal additional context about parameters beyond stating 'audio from a URL'. The schema already documents 'model', 'language', and 'audio_url' with descriptions.

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 specifies the verb 'transcribe', the resource 'audio from a URL', and the model 'Whisper'. It distinctly sets this tool apart from its sibling 'spraay_compute_tts' which performs text-to-speech.

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 description states what the tool does but does not provide explicit guidance on when to use it versus alternatives, nor does it mention when not to use it. The cost is noted but no usage boundaries are given.

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

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