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deepgram_tts

Convert text to speech using Deepgram Aura, save the resulting MP3 file, seal a ProofLink receipt, and return the download URL.

Instructions

Convert text to speech via Deepgram Aura (aura-asteria-en). Saves MP3 to mission-videos/ and seals a ProofLink receipt. Returns mp3_url.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText to convert (max 4000 chars)
voiceNoDeepgram voice model (default: aura-asteria-en)
output_filenameNoOptional output filename (auto-generated if omitted)
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It transparently reveals key side effects: saving an MP3 to a specific directory, sealing a ProofLink receipt, and returning an mp3_url. While it does not cover error handling or prerequisites, it effectively communicates the tool's non-obvious behaviors and outputs.

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 three concise sentences: purpose, side effects, and return value. Each sentence earns its place with no redundancy or filler. The most important action is front-loaded, making it 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 tool with 3 parameters and no output schema, the description provides an unusually complete picture: it specifies the input (text), the processing model, the output file location, the receipt side effect, and the return type (mp3_url). It does not mention potential prerequisites like API keys or error conditions, but given the simplicity and the presence of a schema, this is sufficient. The description covers essentially all key operational aspects.

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 already provides 100% parameter descriptions, so the baseline is met. The description adds contextual information about the output format and destination, but it does not provide additional detail about individual parameters beyond what the schema already states. The description's mention of MP3 and mission-videos/ indirectly informs the output_filename parameter, but not enough to exceed the baseline.

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 'Convert text to speech via Deepgram Aura' with a specific voice model, and further distinguishes itself from siblings like deepgram_transcribe by mentioning the MP3 output saved to mission-videos/ and the ProofLink receipt. It uses a specific action verb and resource, fully differentiating this tool.

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 implies a use case (saving audio to mission-videos) but does not explicitly state when to use this tool versus alternatives like deepgram_blog_audio. It lacks explicit when-to-use or when-not-to-use guidance, so the context is present but not formally articulated.

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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