azure-ai-voicelive-java

Azure AI VoiceLive SDK for Java. Real-time bidirectional voice conversations with AI assistants using WebSocket.

Quality

—

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Quality

Content

65%

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

The body is highly actionable with complete executable Java examples, but it is a long monolithic API reference dumped inline with no bundle files for progressive disclosure and no validation checkpoints in its workflow, capping conciseness, workflow clarity, and progressive disclosure at the mid-band.

Suggestions

Move the detailed API surface (full VoiceLiveSessionOptions setter list, voice configuration, function calling) into a references file (e.g. references/API.md) and keep SKILL.md as a concise overview pointing to it, improving both conciseness and progressive disclosure.

Add explicit validation checkpoints to the Core Workflow (e.g. confirm SESSION_CREATED before sending audio/config, verify response deltas are non-empty before playback) and fold the Error Handling feedback loop into the step sequence.

Trim the generic 'When to Use'/'Limitations' boilerplate ('This skill is applicable to execute the workflow or actions described in the overview.') to specific, useful guidance.

Dimension	Reasoning	Score
Conciseness	The body is code-focused with no padding of concepts Claude already knows, but it is a ~225-line inline dump of the full API surface (all session-option setters, voice types, function calling, error handling) plus generic 'When to Use'/'Limitations' boilerplate, so it is mostly efficient but could be tightened or split; it does not reach the 'lean; every token earns its place' anchor.	2 / 3
Actionability	It provides complete, copy-paste-ready Java examples for each step (start session, configure options, send audio, handle events, voice config, function calling, error handling) with real imports and concrete API calls, matching the 'fully executable code; copy-paste ready' anchor; the readAudioChunk/playAudioChunk placeholders are justified user-supplied helpers.	3 / 3
Workflow Clarity	A numbered Core Workflow (1. Start Session, 2. Configure Session Options, 3. Send Audio Input, 4. Handle Events) gives a clear sequence, but there are no explicit validation checkpoints or an inline error-recovery feedback loop within the workflow, so it sits at 'steps listed but checkpoints missing' rather than the 'explicit validation steps; feedback loops' level.	2 / 3
Progressive Disclosure	No bundle files exist (references/scripts/assets absent) and the entire API reference lives inline in one ~225-line file rather than being split into one-level-deep reference files; it has structure but content that should be separate is inline, matching the 'some structure but could be better organized' anchor and falling short of the well-signaled multi-file overview anchor.	2 / 3
	Total	9 / 12 Passed

Description

57%

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 accurate and distinctly scoped to a specific Azure SDK, but it states only a single capability and omits any 'Use when...' trigger guidance, leaving it mid-band on specificity, trigger terms, and completeness.

Suggestions

Add a 'Use when...' clause listing natural trigger terms users would say (e.g. 'Use when building real-time voice chat, speech conversations, or realtime audio streaming with Azure OpenAI in Java').

List a few more concrete actions beyond the single capability (e.g. 'start sessions, stream PCM16 audio, configure turn detection and voices, handle function calling') to reach the multiple-specific-actions anchor.

Expand trigger-term coverage with common variations such as 'voice chat', 'speech', and 'realtime audio' alongside 'voice conversations'.

Dimension	Reasoning	Score
Specificity	It names the domain ('Azure AI VoiceLive SDK for Java') and one concrete capability ('Real-time bidirectional voice conversations with AI assistants using WebSocket'), but does not list multiple distinct concrete actions, so it stops at the 'names domain and some actions' anchor rather than the 'lists multiple specific concrete actions' level.	2 / 3
Completeness	It clearly answers 'what does this do', but there is no 'Use when...' clause or equivalent explicit trigger guidance; per the judging guidelines a missing trigger clause caps completeness at 2 rather than 3.	2 / 3
Trigger Term Quality	Phrases like 'voice conversations', 'real-time', and 'AI assistants' are reasonably natural, but coverage is thin and missing common variations (e.g. 'voice chat', 'speech', 'realtime audio'); it is above jargon-only but below full natural-term coverage.	2 / 3
Distinctiveness Conflict Risk	'Azure AI VoiceLive SDK for Java' is a narrow, clearly-scoped niche unlikely to trigger for unrelated skills, matching the 'clear niche with distinct triggers; unlikely to conflict' anchor; it is well above the 'somewhat specific but could overlap' level.	3 / 3
	Total	9 / 12 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: sickn33/antigravity-awesome-skills
Commit: 1e7fd2a

Reviewed: 2 days ago

Table of Contents

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