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Canvas plugin architecture patterns, best practices, and implementation templates
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| name | plugin-patterns |
| description | Canvas plugin architecture patterns, best practices, and implementation templates |
This skill provides architectural patterns, best practices, and implementation guidance for building Canvas plugins. It supplements the SDK reference with practical patterns learned from real-world plugins.
Use this skill when you need:
Reference the patterns_context.txt file for detailed patterns and examples.
Canvas SDK reference and documentation. Use whenever a question, claim, or piece of code touches Canvas SDK capabilities, API usage, implementation patterns, or testing — including quick conversational questions ("how do I ingest ADTs?", "what's the import for X?", "does Canvas support Y?"). The bundled docs are the source of truth; do not answer Canvas SDK questions from memory.
FHIR API reference and documentation for Canvas plugins that need to read or write data via FHIR endpoints
This skill should be used when the user asks to "write tests", "create tests", "generate tests", "unit tests", "pytest", "test guidelines", "testing rules", "test standards", "how to test", "test this code", "add tests", "validate tests", "check tests", "improve tests", or when working with Python test files. Provides comprehensive guidelines for creating pytest unit tests with 100% coverage following strict naming conventions, mock patterns, and parametrization standards.
Custom Data anti-patterns and corrections for Canvas plugins - unnecessary compatibility checks, misuse of AttributeHubs vs CustomModels
Database query optimization for Canvas plugins - N+1 detection, prefetch_related, select_related
Security review for plugins acting as FHIR API clients - token management, scope validation, and patient-scoped authorization
