azure-ai-transcription-py
Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.
Install with Tessl CLI
npx tessl i github:sickn33/antigravity-awesome-skills --skill azure-ai-transcription-py88
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
85%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong description that clearly identifies the technology stack, specific capabilities, and when to use it. The main weakness is the trigger term coverage, which could benefit from more natural user language variations like 'audio', 'voice recording', or common file formats.
Suggestions
Add natural user terms like 'audio', 'voice', 'transcribe recordings', '.wav', '.mp3' to improve trigger term coverage
Consider expanding the 'Use for' clause to include phrases users might say, such as 'when converting audio to text' or 'when transcribing meeting recordings'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'real-time and batch speech-to-text transcription with timestamps and diarization'. These are distinct, technical capabilities that clearly describe what the skill does. | 3 / 3 |
Completeness | Clearly answers both what ('Azure AI Transcription SDK for Python' with 'real-time and batch speech-to-text transcription with timestamps and diarization') and when ('Use for...' provides explicit trigger guidance). | 3 / 3 |
Trigger Term Quality | Includes relevant terms like 'transcription', 'speech-to-text', 'timestamps', 'diarization', but missing common user variations like 'audio', 'voice', 'convert speech', 'transcribe', or file extensions like '.wav', '.mp3'. | 2 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with specific technology stack (Azure AI, Python SDK) and clear domain (speech-to-text transcription). Unlikely to conflict with other skills due to the specific platform and feature set mentioned. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-crafted, concise skill that provides actionable code examples for Azure AI Transcription. The main weakness is the lack of error handling guidance and validation steps for transcription operations, which could leave Claude without clear recovery paths when jobs fail or produce unexpected results.
Suggestions
Add error handling examples showing how to check job.status for failures and retry logic for transient errors
Include a validation step showing how to verify transcription results (e.g., checking result.status == 'Succeeded' before accessing transcripts)
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, providing only essential information without explaining concepts Claude already knows. Every section serves a clear purpose with no padding or unnecessary context. | 3 / 3 |
Actionability | Provides fully executable, copy-paste ready code examples for authentication, batch transcription, and real-time streaming. All code snippets are complete and specific. | 3 / 3 |
Workflow Clarity | The skill presents two distinct workflows (batch and real-time) with clear code, but lacks validation checkpoints or error handling guidance. No feedback loops for handling transcription failures or verifying results. | 2 / 3 |
Progressive Disclosure | For a skill of this size (~50 lines), the content is well-organized with clear sections. No external references are needed, and the structure allows easy navigation between authentication, batch, and real-time use cases. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Reviewed
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