aiwg
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Cognitive architecture for AI-augmented software development with structured memory, ensemble validation, and closed-loop correction. FAIR-aligned artifacts, 84% cost reduction via human-in-the-loop, standards adopted by 100+ organizations.
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{
"id": "ralph",
"type": "addon",
"name": "Ralph Loop",
"version": "1.0.0",
"description": "Iterative AI coding loops with automatic recovery - iteration beats perfection",
"core": false,
"autoInstall": false,
"author": "AIWG Contributors",
"license": "MIT",
"repository": "https://github.com/jmagly/aiwg",
"keywords": [
"ralph",
"iteration",
"loop",
"autonomous",
"batch",
"refactor",
"migration",
"wiggum"
],
"researchFoundation": {
"REF-001": "Ralph Wiggum methodology - iterative AI execution with stop hooks",
"REF-002": "BP-6 - Recovery requires execution history",
"REF-003": "Predictable failure with automatic recovery beats unpredictable success"
},
"entry": {
"commands": "commands/",
"skills": "skills/",
"agents": "agents/",
"hooks": "hooks/",
"templates": "templates/",
"docs": "docs/"
},
"commands": [
"ralph",
"ralph-status",
"ralph-abort",
"ralph-resume",
"ralph-reflect",
"ralph-analytics",
"debug-memory",
"execute-feedback"
],
"skills": [
"ralph-loop",
"reflection-injection",
"auto-test-execution"
],
"agents": [
"ralph-loop",
"ralph-verifier"
],
"hooks": [
"ralph-loop",
"ralph-commit",
"post-iteration-reflect",
"pre-return-execution-gate"
],
"templates": [
"ralph-task",
"ralph-completion",
"self-reflection-prompt"
],
"dependencies": {
"required": [],
"optional": ["aiwg-hooks", "aiwg-utils"]
},
"configuration": {
"defaults": {
"maxIterations": 10,
"timeoutMinutes": 60,
"autoCommit": true,
"verboseTrace": false
}
}
}