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azure-ai-transcription-py

Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.

77

3.86x
Quality

76%

Does it follow best practices?

Impact

85%

3.86x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/azure-ai-transcription-py/SKILL.md

The canonical home for this skill is azure-ai-transcription-py in sickn33/agentic-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

68%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.

A concise, largely actionable overview with good installation/auth/code examples for both batch and real-time transcription. The main weaknesses are the absent validation/error-handling steps for batch jobs and a filler 'When to Use' section that adds no guidance.

Suggestions

Add error handling and status checking for the batch workflow (e.g., inspect job status for failure, poll/retry guidance) so the batch flow has validation checkpoints.

Replace the boilerplate 'When to Use' sentence with concrete guidance on when to choose batch vs. real-time and what inputs are supported.

Show how to actually retrieve transcription results and timestamps (the stated selling points), and either drop the bare best-practice bullets like 'Handle streaming backpressure' or link them to concrete patterns.

DimensionReasoningScore

Conciseness

Lean, well-sectioned content with short code blocks and no explanations of concepts Claude already knows; the only trimmable padding is the boilerplate 'When to Use' sentence ('This skill is applicable to execute the workflow or actions described in the overview.'), keeping it just below the anchor-5 fit.

4 / 5

Actionability

Mostly executable guidance: install command, env vars, auth snippet, and runnable-looking batch and streaming code. Minor gaps: the batch example only prints 'result.status' without retrieving transcription text or timestamps, and best practices like 'Handle streaming backpressure' give direction without any how.

4 / 5

Workflow Clarity

Sections present the two transcription modes but there is no sequenced workflow with checkpoints: the batch path shows no job status/failure handling or error-recovery loop, and the batch-operation feedback-loop gap caps this at 3 rather than 4.

3 / 5

Progressive Disclosure

Well-organized single-file skill with sensible sections and no unnecessary external references, matching the simple-skill guidance; minor gaps are the contentless 'When to Use' section and streaming/best-practice details that would fit better in a short reference file.

4 / 5

Total

15

/

20

Passed

Description

75%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 solid description that clearly states the domain and concrete capabilities with an explicit 'Use for...' clause. It would score higher with concrete trigger phrases (audio files, transcribe, .wav) in the 'when' portion and a fuller action list.

Suggestions

Rewrite the 'when' clause with concrete trigger phrases, e.g. 'Use when the user mentions transcribing audio files, speech-to-text, subtitles, or diarization' instead of restating the capabilities.

Add natural synonyms and file extensions (audio, voice, captions, .wav, subtitles) to broaden trigger term coverage.

Phrase capabilities as actions (e.g., 'Transcribes audio files in real time or batch, with timestamps and speaker diarization') for stronger specificity.

DimensionReasoningScore

Specificity

Names the domain ('Azure AI Transcription SDK for Python') and several concrete capabilities ('real-time and batch speech-to-text transcription with timestamps and diarization'), but coverage has minor gaps and capabilities are stated as noun phrases rather than the comprehensive action list of the anchor-5 example.

4 / 5

Completeness

Both 'what' and 'when' are present via the explicit 'Use for...' clause, but the 'when' merely restates the what instead of giving concrete trigger phrases, matching the anchor-4 example ('when' could be more explicit or specific).

4 / 5

Trigger Term Quality

Natural terms like 'speech-to-text', 'transcription', 'real-time', 'batch', and 'diarization' are present, but common variations users would say — 'audio', 'voice', 'captions/subtitles', or file extensions like .wav — are missing.

4 / 5

Distinctiveness Conflict Risk

'Azure AI Transcription SDK for Python' is a clear niche with distinct triggers, but there is minor overlap risk with other speech-to-text or Azure speech skills.

4 / 5

Total

16

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills-claude/skills/azure-ai-transcription-py/SKILL.md

Reviewed

Table of Contents

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