Stop writing prompts. Compile intent into AI systems.
Intent Compiler is a reactive workflow system that turns a high-level goal into a structured, executable plan. You write the goal in plain language. It compiles into step-by-step workflows, or into instruction files like CLAUDE.md, .cursorrules, and AGENTS.md.
Complex technical tasks fail on poorly defined context, shifting requirements, and generic prompts. Intent Compiler works in stages.
- Identifying Intent: Capture the core objective of the user.
- Refining Context: LLMs suggest project types, target audiences, and technical constraints.
- Compiling Behavior: Turn the refined intent into actionable steps or specialized instruction files.
- Smart Suggestions: Field recommendations from an LLM (Project, Audience, Style, Tone), tailored to your intent.
- Reactive Workflows: Run, refine or modify each step on its own.
- Instruction Generator: Exports intents into 6+ specialized formats including
CLAUDE.md,AGENTS.md,.cursorrules, and.windsurfrules. - Multi-Agent Orchestration: Coordinates specialized AI agents for complex system building, with role matching and a skill registry.
- Intelligent Model Orchestration: A 3-tier model strategy (Quality, Efficiency, Speed) that picks the LLM for each sub-task.
- Dynamic Provider Support: Fetches and selects models from OpenRouter, Groq, OpenAI, and Ollama in real time.
- Local LLM Support (Ollama): Private inference on models running on your own machine.
- Project Scan Engine: Detects your project's name and tech stack (Next.js, React, Tailwind, TS) for zero-click context.
- Quality Scoring System: 6-dimensional evaluation (correctness, specificity, executability, safety, compatibility, brevity) with validation gates.
- Vibe Mode: A high-fidelity UI view for fast architectural building with reusable templates.
- Intelligent Questioning: Asks targeted questions to clear up vague intent.
- Step Validation: Execution-time validation with rollback and error recovery.
Intent Compiler is built on a fullstack Next.js (App Router) architecture, tuned for low latency and a high-fidelity UI.
- Frontend (React/Framer Motion): A glassmorphic, reactive interface managed by a central
ContextFormandWorkflowContainer. It usesframer-motionfor micro-animations andz-indexlayering to keep the UI stacked correctly. - Model Orchestration Layer (
lib/aicc): A custom internal abstraction (AICC). It handles multi-provider authentication, model property extraction (context length, capabilities), and dynamic tier-based selection. - Compiler Logic (
lib/contextCompiler): Builds refined prompts, grades result quality, and formats structured output. - API Layer (
app/api): Serverless endpoints for real-time suggestion fetching, workflow compilation, and model list synchronization.
- Framework: Next.js 15 (App Router)
- UI: React 19, Tailwind CSS
- Animations: Framer Motion
- AI Integration: OpenAI SDK, OpenRouter, Groq API
- Validation: Zod (schema validation), AJV (JSON validation)
- Database: SQLite (better-sqlite3 for local storage)
- Export: jsPDF (PDF generation), JSZip (bundle exports)
- Markdown: react-markdown, remark-gfm
- Language: TypeScript 5.8
- Linting: ESLint
/app
/api → Serverless API endpoints
/analysis → Project and repo analysis endpoints
/compilation → Intent compilation and workflow generation
/execution → Step execution and validation
/generation → Instruction file generation (CLAUDE.md, etc.)
/model-selection → Model routing and recommendations
/suggestions → LLM-powered field suggestions
/validation → Quality scoring and validation gates
/workflow → Interactive workflow execution page
/components
/ui → Reusable glassmorphic components
ContextForm.tsx → Main intent entry & context refinement engine
ExecutionPanel.tsx → Step execution interface
FileTree.tsx → Project structure visualization
HistoryPanel.tsx → Workflow history and versioning
InputForm.tsx → Structured input collection
IntelligentQuestionsModal.tsx → AI-driven clarification UI
ModelRecommendationBadge.tsx → Model selection indicators
RepoInput.tsx → Repository URL input with analysis
StepCard.tsx → Individual workflow step component
TierBadge.tsx → Quality/Efficiency/Speed tier indicator
VibeLibrary.tsx → Template browser and selector
WelcomeIntro.tsx → Onboarding and example carousel
WorkflowContainer.tsx → Step-by-step execution orchestrator
/lib
/core → Core utilities (JSON guard, OpenAI, storage)
aicc.ts → AI Control Center - multi-provider abstraction
agentOrchestrator.ts → Multi-agent coordination and dispatch
contextCompiler.ts → Structured prompt building & compilation
contextEngineer.ts → Advanced context refinement pipeline
db.ts → SQLite database interface
dynamicRoles.ts → Role definition and matching system
executionEngine.ts → Workflow execution with rollback support
fileExporter.ts → ZIP, PDF export functionality
instructionAssembler.ts → Multi-format instruction file builder
instructionQuality.ts → Quality scoring for generated instructions
intelligentQuestioner.ts → AI-driven intent clarification
jsonGuard.ts → Robust JSON parsing with fallbacks
knowledgeBase.ts → Domain knowledge and best practices
logger.ts → Structured logging system
modelRouter.ts → Intelligent model selection by task type
phaseWorkflow.ts → Phased workflow state management
projectAnalyzer.ts → Automatic project structure detection
repoAnalyzer.ts → GitHub repository analysis
roleDatabase.ts → Agent role definitions and skills
roleMatcher.ts → Intelligent agent-role matching
schemas.ts → Zod validation schemas
skillsRegistry.ts → Agent capabilities registry
stepQuality.ts → Step-level quality validation
superIntelligentModel.ts → Advanced model orchestration
tierConfig.ts → Tier-based model configuration
types.ts → TypeScript type definitions
validationCheckpoint.ts → Execution validation gates
vibeStorage.ts → Vibe template persistence
- Node.js 18.x or higher
- npm or yarn
- Clone the repository:
git clone https://github.com/PantheraLabs/IntentCompiler.git cd IntentCompiler - Install dependencies:
npm install
- Configure environment variables. Create a
.envfile in the root:(SeeOPENAI_API_KEY=your_openai_key OPENROUTER_API_KEY=your_openrouter_key GROQ_API_KEY=your_groq_key
.env.examplefor all required fields)
Enter a high-level goal on the home screen. Use the Example Carousel for inspiration.
The system suggests a project type, an audience, and constraints. The Smart Suggestion Chips fill the form quickly.
The system automatically optimizes for Speed (suggestions), Efficiency (refinement), or Quality (final compilation). You can override the models in the dropdowns.
- Compile Workflow: Generates a structured execution plan you can run step-by-step.
- Compile Instruction File: Generates a
CLAUDE.mdor.cursorrulesfile from your intent.
Run the development server locally:
npm run devThe app runs at http://localhost:3000.
npm run lint- Support for local LLM providers (Ollama).
- Integrate project context auto-detection/scanning.
- Export workflows directly to JSON/YAML for CLI runners.
- Multi-turn intent refinement (chat-based context building).
- Performance benchmarking for different model tiers.
Copyright (c) 2026 Rishi Praseeth Krishnan. All rights reserved.
This software and its source code are for viewing and reference only. No license is granted to use, copy, modify, distribute, or create derivative works without express written permission. See the LICENSE file for the full restrictive terms.
