azure-speech-to-text

Transcribe audio to text using Azure AI Speech (Fast Transcription REST API). Use when converting audio/video to text, generating subtitles, or processing spoken content in OpenMontage. Optional cloud STT provider — preferred when AZURE_SPEECH_KEY is configured; the local faster-whisper `transcriber` is the default offline path.

Quality

100%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

100%

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

A well-structured tool-usage skill: executable code, a genuinely useful Azure-surface comparison, an explicit fallback path with a success checkpoint, and compact parameter/limits references. Stays lean without explaining concepts Claude already knows.

Dimension	Reasoning	Score
Conciseness	Lean and focused — it assumes Claude knows what STT is and reserves prose for Azure-specific knowledge Claude wouldn't have (the Fast-vs-Batch-vs-SDK table) plus actionable parameters and limits. No padding.	3 / 3
Actionability	Provides copy-paste-ready Python calling registry._tools['azure_stt'] with real parameter values, the exact output schema, and setup shell commands — fully executable, not pseudocode.	3 / 3
Workflow Clarity	Clear sequence (configure env vars → call azure_stt → check result.success → fall back to transcriber) with an explicit success/error checkpoint and a 'Verify timing' spot-check step for the subtitle use case.	3 / 3
Progressive Disclosure	A single well-organized SKILL.md with clearly labeled sections and no bundle files; the content is appropriately self-contained at one level with no nested references.	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.

A tight, third-person description that states concrete capabilities, gives explicit 'Use when' triggers, and cleanly distinguishes itself from the sibling offline transcriber. No fluff or over-claims.

Dimension	Reasoning	Score
Specificity	Names multiple concrete actions — 'Transcribe audio to text', 'converting audio/video to text, generating subtitles, or processing spoken content' — rather than vague language.	3 / 3
Completeness	Explicitly answers both what ('Transcribe audio to text using Azure AI Speech (Fast Transcription REST API)') and when ('Use when converting audio/video to text, generating subtitles, or processing spoken content').	3 / 3
Trigger Term Quality	Covers natural user phrasings ('converting audio/video to text', 'generating subtitles', 'processing spoken content') that a user would actually say when they need this skill.	3 / 3
Distinctiveness Conflict Risk	Clear niche (Azure Fast Transcription) with explicit disambiguation from the local transcriber — 'preferred when AZURE_SPEECH_KEY is configured; the local faster-whisper transcriber is the default offline path'.	3 / 3
	Total	12 / 12 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
metadata_field	'metadata' should map string keys to string values	Warning

	Total	14 / 16 Passed

Repository: calesthio/OpenMontage
Path: .agents/skills/azure-speech-to-text/SKILL.md
Commit: 0af32ce

Reviewed: 1 day ago

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