cosmos-db-python-skill
Build Azure Cosmos DB NoSQL services with Python/FastAPI following production-grade patterns. Use when implementing database client setup with dual auth (DefaultAzureCredential + emulator), service layer classes with CRUD operations, partition key strategies, parameterized queries, or TDD patterns for Cosmos. Triggers on phrases like "Cosmos DB", "NoSQL database", "document store", "add persistence", "database service layer", or "Python Cosmos SDK".
Install with Tessl CLI
npx tessl i github:microsoft/agent-skills --skill cosmos-db-python-skillOverall
score
86%
Does it follow best practices?
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npx tessl skill review --optimize ./path/to/skillValidation 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 an excellent skill description that hits all the marks. It provides specific concrete actions, comprehensive trigger terms covering both technical and natural language, explicit 'Use when' and 'Triggers on' clauses, and a clearly defined niche that distinguishes it from other database-related skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'database client setup with dual auth', 'service layer classes with CRUD operations', 'partition key strategies', 'parameterized queries', 'TDD patterns'. These are precise, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both what ('Build Azure Cosmos DB NoSQL services with Python/FastAPI following production-grade patterns') and when ('Use when implementing...', 'Triggers on phrases like...'). Has explicit trigger guidance. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'Cosmos DB', 'NoSQL database', 'document store', 'add persistence', 'database service layer', 'Python Cosmos SDK'. These span technical and conversational language users might naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with clear niche: specifically Azure Cosmos DB + Python/FastAPI + production patterns. Unlikely to conflict with generic database skills due to specific technology stack and explicit trigger terms. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
72%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-structured skill with excellent actionability and progressive disclosure. The code examples are production-ready and the reference organization is clear. However, it could be more concise by removing the architecture diagram and NFRs section, and would benefit from explicit validation steps in the workflow.
Suggestions
Remove or significantly condense the ASCII architecture diagram and NFRs section - these explain concepts Claude already knows
Add explicit validation checkpoints to the Quick Start workflow (e.g., 'Verify connection before proceeding', 'Test query before implementing full service')
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient but includes some unnecessary elements like the ASCII architecture diagram and the NFRs section which explains concepts Claude already understands. The model hierarchy explanation could be tighter. | 2 / 3 |
Actionability | Provides fully executable Python code examples for client setup, Pydantic models, service layer, and testing. Code is copy-paste ready with proper imports and realistic patterns. | 3 / 3 |
Workflow Clarity | Steps are numbered (1. Client Module, 2. Pydantic Model, 3. Service Layer) but lacks explicit validation checkpoints. No feedback loops for error recovery during setup or when operations fail. | 2 / 3 |
Progressive Disclosure | Excellent structure with concise quick-start content and well-organized one-level-deep references. Clear tables linking to reference files and templates with specific use cases for each. | 3 / 3 |
Total | 10 / 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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