azure-ai-transcription-py
Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.
59
68%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/azure-ai-transcription-py/SKILL.mdQuality
Discovery
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.
This is a strong, concise description that clearly identifies the technology stack (Azure AI, Python SDK), the core capability (speech-to-text transcription), and specific features (real-time, batch, timestamps, diarization). It includes a 'Use for...' clause that provides explicit trigger guidance. The description is well-targeted and uses natural keywords that users working with audio transcription would employ.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'real-time and batch speech-to-text transcription with timestamps and diarization.' These are concrete, well-defined capabilities rather than vague language. | 3 / 3 |
Completeness | Clearly answers both what ('Azure AI Transcription SDK for Python' with 'speech-to-text transcription with timestamps and diarization') and when ('Use for real-time and batch speech-to-text transcription'). The 'Use for...' clause serves as an explicit trigger guidance. | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'Azure', 'transcription', 'speech-to-text', 'timestamps', 'diarization', 'real-time', 'batch', 'Python', 'SDK'. These cover common variations of how users would describe this need. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche: Azure-specific, Python-specific, speech-to-text transcription with specific features (timestamps, diarization). Unlikely to conflict with other skills unless there are multiple speech transcription skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
37%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides a reasonable starting point with concrete authentication and basic transcription code examples, but falls short on workflow clarity — particularly lacking error handling, status polling for batch jobs, and validation steps. The best practices are vague directives without executable guidance, and the boilerplate 'When to Use' and 'Limitations' sections waste tokens without adding value.
Suggestions
Add a complete batch transcription workflow with explicit steps: submit job → poll status → handle errors → retrieve and parse results (including accessing diarization segments and timestamps from the response object).
Replace the vague best practices list with concrete code snippets showing how to access timestamps, handle diarization output, and manage streaming backpressure.
Remove the boilerplate 'When to Use' and 'Limitations' sections, which add no skill-specific information and waste tokens.
Add error handling examples for common failure modes (invalid audio format, authentication failure, job timeout) with retry/recovery patterns.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient with good code examples, but the 'Best Practices' section contains some generic advice Claude would already know (e.g., 'specify language to improve accuracy'), and the 'When to Use' and 'Limitations' sections are boilerplate filler that add no actionable information. | 2 / 3 |
Actionability | Provides concrete code examples for authentication, batch, and real-time transcription, but they are incomplete — no error handling, no example of accessing timestamps or diarization results from the response object, and the best practices list describes what to do without showing how (e.g., 'capture timestamps' with no code). | 2 / 3 |
Workflow Clarity | There is no clear multi-step workflow connecting batch transcription steps (upload → submit → poll → retrieve results), no validation checkpoints for checking job status or handling failures, and no error recovery guidance for common issues like invalid audio formats or expired credentials. | 1 / 3 |
Progressive Disclosure | Content is reasonably organized with clear section headers, but everything is inline with no references to external files. The best practices and limitations could be trimmed or separated, and there are no pointers to advanced topics like custom models, vocabulary customization, or detailed API reference. | 2 / 3 |
Total | 7 / 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 | |
- Repository
- sickn33/antigravity-awesome-skills
- Commit
9e5d4dd
- Reviewed
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