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deepgram-java-audio-intelligence

Use when writing or reviewing Java code in this repo that enables Deepgram intelligence overlays on `/v1/listen` audio transcription - diarization, entity detection, sentiment, summarize, topics, intents, language detection, and redaction. Same endpoint as plain STT, but with extra request fields on `ListenV1RequestUrl` or `MediaTranscribeRequestOctetStream`. Use `deepgram-java-speech-to-text` for plain transcripts and `deepgram-java-text-intelligence` for analysis on existing text. Triggers include "audio intelligence", "diarize", "summarize audio", "sentiment from audio", "topic detection", and "redact".

91

1.13x
Quality

89%

Does it follow best practices?

Impact

100%

1.13x

Average score across 3 eval scenarios

SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

81%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Highly actionable content with executable REST and WebSocket examples, verified field names, and clear decision guidance, organized in a sensible single-file structure with a layered reference hierarchy. The main weakness is redundancy: the field lists and WebSocket-subset facts each appear twice, which could be consolidated for token efficiency.

Suggestions

Merge 'What else the REST request surface supports' into 'Key parameters / API surface' so the 12-field list appears only once.

State the WebSocket-only subset ('diarize, detectEntities, redact; not summarize/topics/intents/detectLanguage') once instead of repeating it in both the WebSocket quick start and the key-parameters section.

Consider moving the product-docs link list into a reference file if the skill grows, keeping SKILL.md as the lean overview.

DimensionReasoningScore

Conciseness

The 12-field REST analysis list is repeated nearly verbatim in 'What else the REST request surface supports' and again in 'Key parameters / API surface', and the WebSocket-subset facts are likewise stated twice; the body is otherwise lean but the duplicated lists go beyond minor trimming.

3 / 5

Actionability

Provides complete, copy-paste-ready Java for both the REST path (full imports, builder, transcribeUrl call) and the WebSocket subset, names verified field lists, and points to real repo example files, covering the common cases.

5 / 5

Workflow Clarity

As a single-purpose skill its action is unambiguous: choose REST vs WebSocket, pick the builder matching the input source (gotcha 7), set overlay fields, and follow the NOVA3 model guidance; no destructive or batch operations exist, so no validation checkpoints are required.

5 / 5

Progressive Disclosure

A single well-sectioned file with a clearly signaled, one-level-deep layered reference stack (in-repo source of truth, OpenAPI/AsyncAPI, Context7, product docs) and an honest note that 'reference.md is absent here'; minor gaps in that the docs-link list and gotchas could move to a reference file as the skill grows.

4 / 5

Total

17

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: concrete capabilities, exact class names, an explicit use-when clause with quoted triggers, and explicit routing away from sibling skills. The only gap is a few missing natural synonyms in the trigger list.

Suggestions

Add trigger synonyms such as 'identify speakers', 'who said what', 'detect language', and 'PII removal' to broaden natural-phrase coverage.

DimensionReasoningScore

Specificity

Names eight concrete capabilities ('diarization, entity detection, sentiment, summarize, topics, intents, language detection, and redaction') plus the exact request classes ('ListenV1RequestUrl or MediaTranscribeRequestOctetStream'), giving comprehensive, concrete coverage of the skill's actions rather than minor-gap coverage.

5 / 5

Completeness

Clearly answers 'what' (enables Deepgram intelligence overlays on /v1/listen with named features and classes) and 'when' ('Use when writing or reviewing Java code in this repo... Triggers include...'), matching the anchor that requires both with concrete trigger phrases.

5 / 5

Trigger Term Quality

Explicit trigger list ('audio intelligence', 'diarize', 'summarize audio', 'sentiment from audio', 'topic detection', and 'redact') covers natural user phrasing well, but misses common synonyms such as 'identify speakers', 'who said what', 'detect language', or 'PII removal', so it falls just short of the comprehensive-synonyms anchor.

4 / 5

Distinctiveness Conflict Risk

Scoped to audio-intelligence overlays in this Java repo and explicitly disambiguates sibling skills ('Use deepgram-java-speech-to-text for plain transcripts and deepgram-java-text-intelligence for analysis on existing text'), giving a clear niche with minimal conflict risk.

5 / 5

Total

19

/

20

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

deepgram/deepgram-java-sdk

Path

.agents/skills/deepgram-java-audio-intelligence/SKILL.md

Reviewed

Table of Contents

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