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deepgram-go-speech-to-text

Use when writing or reviewing Go code in this repo that transcribes prerecorded audio with Listen v1 REST or streams live audio with Listen v1 WebSockets. Route text generation to deepgram-go-text-to-speech, text analysis to deepgram-go-text-intelligence, audio analytics overlays to deepgram-go-audio-intelligence, and Flux or other v2 conversational work to deepgram-go-conversational-stt.

71

Quality

86%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

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 well-structured SDK skill with strong actionability through complete, executable Go examples and excellent progressive disclosure via layered references. The main weaknesses are minor verbosity (pseudo-code comments, the central skills section) and a lack of explicit validation/error-recovery steps in the WebSocket streaming workflow, which is a moderately risky operation.

Suggestions

Add explicit validation/error-recovery steps for the WebSocket workflow (e.g., check connection health, handle reconnection on failure, verify transcript receipt before finalizing).

Trim the pseudo-code comments in the WebSocket example and replace with a concrete, minimal audio-writing loop or remove entirely with a pointer to the microphone example files.

DimensionReasoningScore

Conciseness

The skill is mostly efficient but has some unnecessary verbosity. The pseudo-code comments in the WebSocket example add bulk, and the authentication section explains env-backed defaults which Claude can infer. The 'Central product skills' section at the bottom is somewhat tangential. However, the routing table at the top and the key parameters section are well-structured and earn their tokens.

2 / 3

Actionability

Both the prerecorded REST and live WebSocket examples are fully executable Go programs with correct import paths, proper error handling, and copy-paste-ready structure. Key parameters, constructor families, and lifecycle methods are concretely specified with exact function names and field names.

3 / 3

Workflow Clarity

The WebSocket lifecycle (Connect → Start → write audio → Finalize → Stop) is outlined but lacks explicit validation checkpoints. The prerecorded flow is straightforward. However, there's no error recovery guidance for WebSocket reconnection scenarios despite referencing reconnect test files, and the streaming pseudo-code comments are vague rather than providing a concrete validation loop.

2 / 3

Progressive Disclosure

The skill has excellent layered structure: quick start examples inline, a clear routing table to sibling skills, a well-organized 'API reference (layered)' section pointing to in-repo files and external docs at one level deep, and example file paths for deeper exploration. Navigation is clear and references are well-signaled.

3 / 3

Total

10

/

12

Passed

Description

100%

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 an excellent skill description that clearly defines its scope (Go code for Deepgram Listen v1 speech-to-text via REST and WebSockets), provides explicit 'Use when' guidance, and proactively routes adjacent tasks to other named skills. The routing clauses are particularly strong for reducing conflict risk in a multi-skill environment. The description is concise yet comprehensive.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: transcribing prerecorded audio with Listen v1 REST, streaming live audio with Listen v1 WebSockets, and explicitly routes other tasks (text generation, text analysis, audio analytics, conversational work) to other skills.

3 / 3

Completeness

Clearly answers both 'what' (transcribes prerecorded audio via REST, streams live audio via WebSockets) and 'when' (opens with 'Use when writing or reviewing Go code in this repo that...'). Also explicitly defines negative boundaries by routing other tasks elsewhere.

3 / 3

Trigger Term Quality

Includes strong natural keywords users would say: 'Go code', 'transcribes', 'prerecorded audio', 'streams live audio', 'Listen v1', 'REST', 'WebSockets', plus routing terms like 'text-to-speech', 'text intelligence', 'audio intelligence', 'conversational'. These cover the domain well.

3 / 3

Distinctiveness Conflict Risk

Exceptionally distinctive — explicitly delineates its scope (Listen v1 STT) and routes competing tasks to named sibling skills (deepgram-go-text-to-speech, deepgram-go-text-intelligence, deepgram-go-audio-intelligence, deepgram-go-conversational-stt), making conflicts very unlikely.

3 / 3

Total

12

/

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
deepgram/deepgram-go-sdk
Reviewed

Table of Contents

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