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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.

76

3.86x
Quality

68%

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/antigravity-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

37%Scale 1-3

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 completeness—particularly lacking error handling, result processing (timestamps, speaker labels), and validation steps for batch jobs. The 'Best Practices' section is generic, and the 'When to Use' section is a meaningless placeholder that should be removed.

Suggestions

Add error handling and status-checking workflow for batch transcription (e.g., polling job status, handling failures, retrying), and show how to access diarization results (speaker labels, timestamps) from the result object.

Remove the placeholder 'When to Use' section and trim generic best practices that Claude already knows (e.g., 'specify language to improve accuracy').

Add a complete example showing how to extract timestamps and speaker labels from transcription results, since these are called out in the skill description but never demonstrated.

Include validation/verification steps such as checking job.status before accessing results and handling streaming connection errors.

DimensionReasoningScore

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' section is a meaningless placeholder that wastes tokens.

2 / 3

Actionability

Provides concrete code examples for authentication, batch, and real-time transcription, but key details are missing: how to access individual utterances with timestamps, how to retrieve diarization speaker labels from results, and how to properly close streaming sessions. The examples show setup but not result processing.

2 / 3

Workflow Clarity

Batch and real-time transcription are multi-step processes but are presented as isolated code snippets without sequencing, error handling, or validation. There's no guidance on checking job status, handling failures, retrying, or verifying transcription output quality.

1 / 3

Progressive Disclosure

Content is reasonably organized with clear section headers, but everything is inline in a single file. For a skill covering both batch and real-time transcription with diarization and timestamps, separate reference files for advanced configurations or API details would improve navigation. The structure is adequate but not optimized.

2 / 3

Total

7

/

12

Passed

Description

100%Scale 1-3

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 would be easily distinguishable from other skills in a large collection.

DimensionReasoningScore

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 due to the narrow domain focus.

3 / 3

Total

12

/

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.

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

10

/

11

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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