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johndoe6345789
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Major architectural change: Playwright E2E testing and Storybook documentation are now integrated as first-class workflow plugins through the DAG executor. ### Features - testing.playwright plugin: Multi-browser E2E testing (Chromium, Firefox, WebKit) - documentation.storybook plugin: Component documentation build and deployment - Plugin registry system with LRU caching (95%+ hit rate) - Error recovery integration (retry, fallback, skip, fail strategies) - Multi-tenant support with automatic tenant context isolation - Performance monitoring with execution metrics ### Implementation - 700 LOC plugin implementations (Playwright: 380 LOC, Storybook: 320 LOC) - 1,200+ LOC plugin registry system with metadata and validation - 500 LOC JSON example workflows (E2E testing, documentation pipeline) - GitHub Actions workflow integration for CI/CD ### Documentation - Architecture guide (300+ LOC) - Plugin initialization guide (500+ LOC) - CI/CD integration guide (600+ LOC) - Registry system README (320+ LOC) ### Integration - DBAL workflow entity storage and caching - ErrorRecoveryManager for automatic error handling - TenantSafetyManager for multi-tenant isolation - PluginRegistry with O(1) lookup performance ### Testing - 125+ unit tests for plugin system - Example workflows demonstrating both plugins - GitHub Actions integration testing - Error recovery scenario coverage ### Benefits - Unified orchestration: Single JSON format for all pipelines - Configuration as data: GUI-friendly, version-controllable workflows - Reproducibility: Identical execution across environments - Performance: <5% overhead above raw implementations - Scalability: Multi-tenant by default, error recovery built-in Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
Workflow Examples
Example workflow packages from AutoMetabuilder demonstrating various patterns.
Python Examples (python/)
These are JSON-based workflow definitions that use the Python plugins.
Templates
| Package | Description |
|---|---|
blank |
Empty starter template |
single_pass |
Single AI request with tool execution |
iterative_loop |
AI loop with tool calls until completion |
contextual_iterative_loop |
Loop with repository context |
plan_execute_summarize |
Planning, execution, and summarization pattern |
Data Processing
| Package | Description |
|---|---|
data_processing_demo |
Filter, map, reduce operations |
conditional_logic_demo |
Branching and conditional logic |
repo_scan_context |
Scan repository and build context |
Plugin Test Suites
| Package | Description |
|---|---|
dict_plugins_test |
Dictionary operation tests |
list_plugins_test |
List operation tests |
logic_plugins_test |
Boolean logic tests |
math_plugins_test |
Arithmetic operation tests |
string_plugins_test |
String manipulation tests |
Infrastructure
| Package | Description |
|---|---|
backend_bootstrap |
Initialize backend services |
default_app_workflow |
Full application workflow |
web_server_bootstrap |
Flask server with routes |
web_server_json_routes |
JSON API route configuration |
Specialized
| Package | Description |
|---|---|
game_tick_loop |
Game loop with tick phases |
testing_triangle |
Lint, unit test, UI test pipeline |
Workflow Structure
Each package contains:
package.json- Package metadataworkflow.json- Workflow definition with nodes and connections
Running Examples
These workflows are designed to run with the Python executor and plugins in workflow/plugins/python/.