azure-ai-search-python
Clean code patterns for Azure AI Search Python SDK (azure-search-documents). Use when building search applications, creating/managing indexes, implementing agentic retrieval with knowledge bases, or working with vector/hybrid search. Covers SearchClient, SearchIndexClient, SearchIndexerClient, and KnowledgeBaseRetrievalClient.
Install with Tessl CLI
npx tessl i github:microsoft/agent-skills --skill azure-ai-search-pythonOverall
score
93%
Does it follow best practices?
Validation for skill structure
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 well-crafted skill description that excels across all dimensions. It provides specific capabilities, includes a clear 'Use when...' clause with natural trigger terms, names concrete SDK components, and establishes a distinct niche that won't conflict with other skills. The third-person voice and technical specificity make it highly effective for skill selection.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'building search applications, creating/managing indexes, implementing agentic retrieval with knowledge bases, working with vector/hybrid search' and names specific clients (SearchClient, SearchIndexClient, SearchIndexerClient, KnowledgeBaseRetrievalClient). | 3 / 3 |
Completeness | Clearly answers both what ('Clean code patterns for Azure AI Search Python SDK') and when ('Use when building search applications, creating/managing indexes, implementing agentic retrieval...') with explicit trigger guidance. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'Azure AI Search', 'Python SDK', 'search applications', 'indexes', 'agentic retrieval', 'knowledge bases', 'vector search', 'hybrid search', plus specific client class names that developers would reference. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with clear niche: specifically targets Azure AI Search Python SDK (azure-search-documents), names exact client classes, and focuses on specific search patterns. Unlikely to conflict with generic search or other cloud provider skills. | 3 / 3 |
Total | 12 / 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 high-quality skill with excellent conciseness and actionability. The code examples are complete, executable, and well-organized with clear section headers and reference tables. The main weakness is the lack of explicit validation steps and feedback loops for multi-step operations like index creation and batch document uploads.
Suggestions
Add validation checkpoint after index creation (e.g., verify index exists before uploading documents)
Include error handling/retry guidance for SearchIndexingBufferedSender batch operations with explicit feedback loop
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, providing only necessary code examples and tables without explaining concepts Claude already knows. No padding or unnecessary context about what Azure AI Search is or how SDKs work. | 3 / 3 |
Actionability | All code examples are fully executable and copy-paste ready with proper imports. Covers authentication, index creation, document operations, search patterns, async usage, and error handling with complete, working code. | 3 / 3 |
Workflow Clarity | While individual operations are clear, the skill lacks explicit validation checkpoints for multi-step processes like index creation followed by document upload. No feedback loops for error recovery in batch operations with SearchIndexingBufferedSender. | 2 / 3 |
Progressive Disclosure | Well-structured with clear sections, appropriate use of tables for quick reference, and properly signals the external reference for agentic retrieval details. Content is appropriately split between overview and detailed reference. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
87%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' field is not a dictionary | Warning |
license_field | 'license' field is missing | Warning |
Total | 14 / 16 Passed | |
- Reviewed
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