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deepgram-python-audio-intelligence

Use when writing or reviewing Python code in this repo that calls Deepgram audio analytics overlays on `/v1/listen` - summarize, topics, intents, sentiment, diarize, redact, detect_language, entity detection. Same endpoint as plain STT but with analytics params. Covers both REST (`client.listen.v1.media.transcribe_url`/`transcribe_file`) and the WSS-supported subset (`client.listen.v1.connect`). Use `deepgram-python-speech-to-text` for plain transcription, `deepgram-python-text-intelligence` for analytics on already-transcribed text. Triggers include "diarize", "summarize audio", "sentiment from audio", "redact PII", "topic detection audio", "audio intelligence", "detect language audio".

80

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

100%

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

The SKILL.md body is well-organized, executable, and concise, with a clear feature-availability matrix, scenario-based quick starts, and a layered reference section. The only gap is that some referenced local files (reference.md, examples/, tests/wire/) are not present in the bundle, which is an accuracy issue rather than a structural one.

Suggestions

Verify or create the referenced local bundle files (reference.md, examples/15-transcription-advanced-options.py, tests/wire/test_listen_v1_media.py) so the layered navigation pointers resolve to real files.

Consider noting which referenced docs/recipes live in the central 'deepgram/skills' pack vs. this SDK skill, to keep the one-level-deep reference boundary crisp.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence: it states SDK-specific facts and parameters without explaining basic concepts (e.g. what a transcript or diarization is), and every section earns its place. Not score 2 because there is no unnecessary padding despite covering several scenarios.

3 / 3

Actionability

Multiple fully executable, copy-paste-ready code blocks show real SDK method calls, concrete parameters, and exact result-access paths (e.g. r.channels[0].alternatives[0].transcript), matching the 'fully executable code/commands' anchor. Not score 2 because nothing is pseudocode or abstract.

3 / 3

Workflow Clarity

Each scenario (REST URL, REST file, diarization timing, WSS subset) is laid out as a clear, unambiguous quick start, and the Gotchas section provides guardrails for fragile cases. This is a code-reference skill without destructive/batch operations, so the validation-feedback-loop cap does not apply. Not score 2 because the per-scenario sequences are complete and explicit.

3 / 3

Progressive Disclosure

A clear 'API reference (layered)' section gives well-signaled, one-level-deep pointers (in-repo reference.md, OpenAPI/AsyncAPI URLs, Context7 ID, product docs, example/test files) with content appropriately split rather than inlined. Note: the referenced local bundle files (reference.md, examples/, tests/wire/) are not present in this review bundle, which is an accuracy gap rather than a disclosure-structure flaw.

3 / 3

Total

12

/

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.

The description is specific, well-triggered, and clearly differentiated from sibling skills, answering both what the skill does and when to use it. It is a strong, concise trigger description with no padding.

DimensionReasoningScore

Specificity

Lists multiple specific concrete analytics actions (summarize, topics, intents, sentiment, diarize, redact, detect_language, entity detection) plus named REST/WSS SDK methods, matching the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

Explicitly answers both 'what' (analytics overlays on /v1/listen via REST and WSS) and 'when' (a 'Use when...' clause plus explicit trigger terms), matching the top anchor that requires both with explicit triggers.

3 / 3

Trigger Term Quality

An explicit trigger list captures natural phrases a user would say ('summarize audio', 'sentiment from audio', 'redact PII', 'topic detection audio', 'audio intelligence', 'detect language audio'), giving good coverage of natural terms.

3 / 3

Distinctiveness Conflict Risk

Carves a clear niche (audio intelligence analytics, distinct from plain STT) and explicitly redirects to sibling skills (speech-to-text, text-intelligence), making it unlikely to trigger for the wrong skill.

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
deepgram/deepgram-python-sdk
Reviewed

Table of Contents

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