deepgram-go-text-to-speech
Use when writing or reviewing Go code in this repo that synthesizes audio with Speak v1 REST or Speak WebSockets. Route transcription work to deepgram-go-speech-to-text, voice conversation runtime work to deepgram-go-voice-agent, and repository maintenance work to deepgram-go-maintaining-sdk.
85
81%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
89%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description with excellent completeness and distinctiveness. It clearly defines its scope (Go code for Deepgram Speak audio synthesis) and explicitly routes adjacent work to sibling skills, minimizing conflict risk. The main weakness is that it could list more specific concrete actions beyond 'writing or reviewing' to better convey the full range of capabilities.
Suggestions
Add more specific concrete actions such as 'configure audio output parameters, manage WebSocket streaming connections, handle REST API responses' to improve specificity.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | It names the domain (Go code, audio synthesis with Speak v1 REST or Speak WebSockets) and mentions some actions (writing, reviewing), but doesn't list specific concrete actions like 'configure audio output formats, handle streaming responses, manage WebSocket connections'. | 2 / 3 |
Completeness | Clearly answers both 'what' (writing/reviewing Go code for audio synthesis with Speak v1 REST or WebSockets) and 'when' (explicit 'Use when' clause). Additionally provides explicit routing guidance for related but distinct skills, which strengthens the 'when' dimension. | 3 / 3 |
Trigger Term Quality | Includes strong natural trigger terms: 'Go code', 'synthesizes audio', 'Speak v1 REST', 'Speak WebSockets', 'text-to-speech' is implied via 'Speak'. The routing clauses also include useful disambiguation terms like 'transcription', 'voice conversation', 'speech-to-text'. Users asking about TTS or audio synthesis in Go would naturally use these terms. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with explicit routing to sibling skills (deepgram-go-speech-to-text, deepgram-go-voice-agent, deepgram-go-maintaining-sdk), clearly carving out its niche as the text-to-speech/Speak skill and actively preventing conflicts with related Deepgram Go skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, well-structured SDK skill with excellent actionability through complete, executable Go examples for both REST and WebSocket TTS. The progressive disclosure is strong with a layered reference section. Main weaknesses are minor verbosity (full boilerplate in both examples, tangential 'central product skills' section) and lack of validation/error-recovery guidance in the workflows.
Suggestions
Add a brief validation step after REST synthesis (e.g., check file exists, verify file size > 0) and after WebSocket connection (e.g., confirm audio frames received) to improve workflow clarity.
Consider trimming the full `package main` / `func main()` boilerplate from at least one example, or consolidating into a single example with comments showing the WS variant, to reduce token usage.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient but includes some unnecessary verbosity — the full `package main` boilerplate in both examples adds bulk, and the 'Central product skills' section at the bottom is tangential. The key parameters and gotchas sections are lean and useful. | 2 / 3 |
Actionability | Both REST and WebSocket examples are fully executable, copy-paste ready Go programs with correct imports and error handling. Key parameters, constructors, and methods are concretely listed. | 3 / 3 |
Workflow Clarity | The quick start examples show clear sequences (create client → call method → handle result), but there are no explicit validation checkpoints — no guidance on verifying the output file was created, checking audio format correctness, or handling common failure modes like invalid API keys or connection drops. | 2 / 3 |
Progressive Disclosure | Content is well-structured with a clear overview, quick start, key parameters, and a layered API reference section pointing to in-repo files, OpenAPI/AsyncAPI specs, and external docs. References are one level deep and clearly signaled with paths and URLs. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- deepgram/deepgram-go-sdk
- Commit
b7c92f4
- Reviewed
Table of Contents
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