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Load [`AGENTS.md`](./AGENTS.md) first** — it's the agent guide with repo layout, routing, conventions, and testing.\n\nWelcome to **ICIL — Intelligence Campus Interactive Library**, an *intelligence layer* designed as a sacred reference for AI agents. Each directory is a **faculty of knowledge**, and each `.md` file is a **course** that can be loaded by AI agents as deep contextual knowledge.\n\n---\n\n## ⚡ Quick Start\n\n```bash\n# Clone \u0026 install\ngit clone https://github.com/kandarlubis31/ICIL.git \u0026\u0026 cd ICIL \u0026\u0026 npm install\n\n# Route any design/dev prompt to relevant courses\nnode load-context.js \"build an accessible landing page\"\n\n# List all 29 faculties with course counts\nnode load-context.js --list\n\n# Start MCP server for Claude Desktop / Cursor\nnode mcp-server.js\n\n# Run CI validation\nnode ci-validate.js --with-eval\n```\n\n\u003e **AI Agent?** Load [`AGENTS.md`](./AGENTS.md) first — it's the single source of truth for repo conventions.  \n\u003e **MCP User?** Configure Claude Desktop with [`mcp-server.js`](./mcp-server.js) — 10 tools, zero API keys.\n\n---\n\n## 📈 Eval Progress\n\n\u003e Auto-router precision \u0026 recall journey — from 54.4% P@3 to 72.8% across 5 tuning rounds.\n\n### Precision@3 \u0026 Recall@3\n\n```mermaid\nxychart-beta\n  title \"P@3 \u0026 R@3 Progress — ICIL Auto-Router\"\n  x-axis [\"v24.1.0\", \"v25.0.0\", \"v25.0.3\", \"v25.0.5\"]\n  y-axis \"%\" 50 --\u003e 100\n  line [54.4, 59.3, 64.9, 72.8]\n  line [77.9, 85.9, 84.5, 94.4]\n```\n\n\u003e Top line: P@3 · Bottom line: R@3 — CI gate threshold at 70%\n\n### MRR (Mean Reciprocal Rank)\n\n```mermaid\nxychart-beta\n  title \"MRR Progress — ICIL Auto-Router\"\n  x-axis [\"v24.1.0\", \"v25.0.0\", \"v25.0.5\"]\n  y-axis \"MRR\" 0.65 --\u003e 1.0\n  line [0.731, 0.809, 0.922]\n```\n\n\u003e CI threshold at 0.65 ✅ — current 0.922 well above\n\n| Release | P@3 | R@3 | MRR | Key Event |\n|---------|------|-----|-----|-----------|\n| v24.1.0 | 54.4% | 77.9% | 0.731 | Eval infrastructure launched |\n| v25.0.0 | 59.3% | 85.9% | 0.809 | Design Ethics faculty + baseline |\n| v25.0.3 | 64.9% | 84.5% | — | DUPLICATE HIGH → 0 + noise removal |\n| **v25.0.5** | **72.8%** | **94.4%** | **0.922** | Phase 1 LOW tightening + 17 dup keywords fixed |\n\n---\n\n## 🏛️ Campus Structure\n\n```\ninteligence_mas-aul/\n├── README.md                   # 🗺️ Campus map (you are here!)\n├── index.json                  # 🤖 Machine-readable index for AI agents\n├── campus-core.js              # 🔧 Shared library\n├── load-context.js             # 🔧 Auto-router CLI tool\n├── mcp-server.js               # 🔌 MCP server (10 tools, v3)\n├── CONTEXT.md                  # 💾 Session save state\n├── CHANGELOG.md                # 📋 Version history\n├── CONTRIBUTING.md             # 🤝 Contribution guide\n├── LICENSE                     # ⚖️ MIT License\n├── warna/                      # 🎨 Faculty of Color\n│   ├── README.md\n│   ├── 01-color-theory-basics.md\n│   ├── 02-color-harmony.md\n│   ├── 03-color-psychology.md\n│   ├── 04-color-in-culture.md\n│   ├── 05-digital-color-models.md\n│   ├── 06-color-accessibility.md\n│   ├── 07-palette-generation.md\n│   ├── 08-color-design-systems.md\n│   └── 09-advanced-color-composition.md\n├── ux-psikologi/               # 🧠 Faculty of UX Psychology\n│   └── (7 courses)\n├── ux-writing/                 # ✍️ Faculty of UX Writing\n│   └── (7 courses)\n├── tipografi/                  # 🔤 Faculty of Typography\n│   └── (7 courses)\n├── layout/                     # 📐 Faculty of Layout \u0026 Grid\n│   └── (7 courses)\n├── design-patterns/            # 🧩 Faculty of Design Patterns\n│   └── (8 courses)\n├── animasi/                    # ✨ Faculty of Animation \u0026 Motion\n│   └── (7 courses)\n├── branding/                   # 🏷️ Faculty of Branding\n│   └── (7 courses)\n├── aksesibilitas/              # ♿ Faculty of Accessibility\n│   └── (7 courses)\n├── improvement/                # 🔧 Faculty of Improvement\n│   └── (7 courses)\n├── kognisi/                    # 🧠 Faculty of Human Cognition\n│   └── (7 courses)\n├── mobile-ux/                  # 📱 Faculty of Mobile UX \u0026 Touch Design\n│   └── (7 courses)\n├── data-viz/                   # 📊 Faculty of Data Visualization\n│   └── (7 courses)\n├── design-systems/             # 🛠️ Faculty of Design Systems \u0026 Tools\n│   └── (7 courses)\n├── conversational-ui/          # 💬 Faculty of Conversational UI \u0026 Voice\n│   └── (8 courses)\n├── strategic-design/           # 🧭 Faculty of Strategic Design \u0026 Product Thinking\n│   └── (7 courses)\n├── service-design/             # 🌐 Faculty of Service Design \u0026 Systems\n│   └── (7 courses)\n├── software-engineering/       # ⚙️ Faculty of Software Engineering\n│   └── (9 courses)\n├── devops-infra/               # 🐳 Faculty of DevOps \u0026 Infrastructure\n│   └── (7 courses)\n├── database-management/        # 🗄️ Faculty of Database Management\n│   └── (7 courses)\n├── ai-integration/             # 🤖 Faculty of AI Integration \u0026 LLM\n│   └── (10 courses)\n├── security/                   # 🔐 Faculty of Security \u0026 App Defense\n│   └── (9 courses)\n├── performance/                # ⚡ Faculty of Performance Engineering\n│   └── (7 courses)\n├── testing-qa/                 # 🧪 Faculty of Testing \u0026 Quality Assurance\n│   └── (7 courses)\n├── dx/                         # 🖥️ Faculty of Developer Experience\n│   └── (7 courses)\n├── ia/                         # 🗂️ Faculty of Information Architecture\n│   └── (7 courses)\n├── agentic-engineering/        # 🤖 Faculty of Agentic Engineering \u0026 Orchestration\n│   └── (9 courses)\n├── ux-research/                # 🔬 Faculty of UX Research \u0026 Discovery\n│   └── (7 courses)\n└── design-ethics/              # ⚖️ Faculty of Design Ethics\n    └── (7 courses)\n```\n\n---\n\n## 🎯 Philosophy\n\nThis campus is built on principles:\n\n| Principle | Meaning |\n|-----------|---------|\n| **Self-contained** | Each file stands alone as AI agent context |\n| **Deep, not wide** | Each course is deep, not surface-level |\n| **Agent-first** | Written in an optimal format for AI agent loading |\n| **Research-backed** | All content based on research, not guesswork |\n| **Practical** | Theory + practical examples + code |\n\n---\n\n## 🚀 How to Use\n\n### For AI Agents — Auto-Router CLI\n\nUse the built-in CLI tool to automatically find relevant courses based on a user prompt:\n```bash\nnode load-context.js \"create a luxury landing page with elegant design\"\nnode load-context.js \"make accessible forms for screen readers\" --json\nnode load-context.js --list\nnode load-context.js --interactive\n```\n\nOr load `.md` files manually as system prompt or context injection:\n```\nYou are an AI designer. Use knowledge from the color faculty:\n[load warna/01-color-theory-basics.md]\n[load warna/02-color-harmony.md]\n```\n\n### For Humans\nJust read the files in order per faculty. Each file lists its prerequisites at the top.\n\n### For Contributors\nRead [`CONTRIBUTING.md`](./CONTRIBUTING.md) for the course template, naming conventions, and PR checklist.\nSee [`CHANGELOG.md`](./CHANGELOG.md) for version history.\n\n---\n\n## 📚 Available Faculties\n\n### 🎨 Faculty of Color — `warna/`\nComprehensive color knowledge: from basic theory, harmony, psychology, cultural meanings, digital models, accessibility, to palette generation techniques and advanced composition.\n\n**9 Courses** | **Level: Beginner → Advanced**\n\n### 🧠 Faculty of UX Psychology — `ux-psikologi/`\nCognitive psychology behind UX: cognitive biases, UX laws (Fitts, Hick, Miller, Jakob), Gestalt principles, ethical persuasion, dark patterns, and gamification.\n\n**7 Courses** | **Level: Intermediate → Advanced**\n\n### ✍️ Faculty of UX Writing — `ux-writing/`\nThe art of writing words in interfaces: microcopy, voice \u0026 tone, error states, onboarding, language accessibility, localization, and content design systems.\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🔤 Faculty of Typography — `tipografi/`\nDigital typography: typeface anatomy, type scale \u0026 hierarchy, font pairing, readability, spacing, variable fonts, and web typography performance.\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 📐 Faculty of Layout \u0026 Grid — `layout/`\nDigital layout: grid systems, CSS Grid (basics to subgrid), Flexbox, responsive breakpoints, visual composition, golden ratio, and spacing systems.\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🧩 Faculty of Design Patterns — `design-patterns/`\nComplete UI patterns catalog: modal/drawer/popover, form design, navigation, search, data display, feedback states, selection inputs, and complex components.\n\n**8 Courses** | **Level: Intermediate → Advanced**\n\n### ✨ Faculty of Animation \u0026 Motion — `animasi/`\nFull motion design spectrum: Disney's 12 principles applied to UI, easing curves \u0026 timing, CSS transitions \u0026 keyframes, micro-interactions, page transitions (View Transitions API), scroll animations, and loading \u0026 skeleton screens.\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🏷️ Faculty of Branding — `branding/`\nComplete brand-building journey: from foundational strategy (purpose, vision, positioning) through visual identity (logos, color, typography, systems), verbal identity (voice, tone, naming), brand guidelines, touchpoint orchestration, to brand evolution and competitive positioning.\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### ♿ Faculty of Accessibility — `aksesibilitas/`\nComplete accessibility spectrum: WCAG foundations (POUR, conformance levels, legal frameworks), semantic HTML, ARIA roles/states/properties, keyboard navigation \u0026 focus management, accessible forms \u0026 inputs, screen reader testing, and advanced inclusive design patterns for cognitive, visual, motor, and auditory disabilities.\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🔧 Faculty of Improvement — `improvement/`\nThe **meta-faculty** that ties the campus together. Teaches AI agents *how to improve* any project systematically: audit → analyze → prioritize → execute → verify. When a user says \"improve this project,\" the agent loads this faculty first to learn the methodology, then loads relevant domain faculties for specific fixes. Includes the end-to-end **ICIL Improvement Protocol**.\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🧠 Faculty of Human Cognition — `kognisi/`\nThe **foundational science faculty** — how the human brain actually works. Covers cognitive architecture (information processing, brain regions, cognitive load), dual process theory (System 1 \u0026 System 2), perception \u0026 attention (selective attention, inattentional blindness, change blindness), memory systems (sensory, working, long-term, forgetting curve, false memories), decision making (bounded rationality, heuristics, prospect theory, nudge theory), problem solving \u0026 creativity (insight, divergent thinking, flow state, constraints), and language/emotion/metacognition (Sapir-Whorf, embodied cognition, Damasio, Flavell, neuroplasticity). This faculty provides the SCIENCE behind all other faculties.\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 📱 Faculty of Mobile UX \u0026 Touch Design — `mobile-ux/`\nComplete mobile UX spectrum: mobile-first principles \u0026 progressive enhancement, touch targets \u0026 gesture design (swipe, pinch, long-press, Fitts' Law on mobile), navigation patterns (bottom nav, tab bars, hamburger menu, FAB, bottom sheets), thumb zone ergonomics \u0026 one-handed design, mobile forms \u0026 input optimization (keyboard-aware layouts, autocomplete, floating labels), mobile animations \u0026 haptics (spring animations, pull-to-refresh, haptic feedback patterns), and responsive/adaptive mobile layouts (container queries, foldables, safe areas, content-driven breakpoints).\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 📊 Faculty of Data Visualization — `data-viz/`\nComplete data visualization spectrum: from the grammar of graphics and visual encoding theory (marks \u0026 channels, preattentive processing, data-ink ratio) through chart selection (decision trees, 15+ chart types with use cases and pitfalls), color science for data (ColorBrewer, perceptual uniformity, semantic color), dashboard design (operational/analytical/strategic patterns, KPI cards, drill-down), interactive dynamics (tooltips, brushing \u0026 linking, zoom/pan, real-time streaming), data storytelling \u0026 narrative (Martini glass, scrollytelling, annotation layers), to accessible data visualization (colorblind-safe palettes, screen reader patterns, alt text for charts, sonification, keyboard navigation).\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🛠️ Faculty of Design Systems \u0026 Tools — `design-systems/`\nComplete design system lifecycle: from foundations (build vs buy, atomic design, maturity model) through tokens (W3C DTCG, Style Dictionary, multi-platform), component library, Figma workflows, governance, multi-brand theming, to ROI measurement.\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 💬 Faculty of Conversational UI \u0026 Voice — `conversational-ui/`\nComplete conversational design spectrum: from fundamentals (Grice's maxims, chat vs voice, cooperative flow) through NLU architecture (intents, entities, training data, confidence thresholds, slot filling), chatbot UX patterns (greetings, quick replies, typing indicators, rich messages, carousels, human handoff), voice UI design (wake words, confirmation strategies, earcons, SSML), error recovery (no-match ladder, misrecognition defense, graceful degradation), personality \u0026 tone (brand alignment, tone mapping, humor guidelines, cultural adaptation), to multi-modal interfaces (voice + screen + touch, device adaptation, conversation continuity).\n\n**8 Courses** | **Level: Beginner → Advanced**\n\n### 🧭 Faculty of Strategic Design \u0026 Product Thinking — `strategic-design/`\nThe **strategic thinking faculty** — teaches AI agents how to think like product leaders. Covers Design Thinking \u0026 the Double Diamond (divergent/convergent process), problem discovery \u0026 framing (Jobs-to-be-Done, How Might We, Amazon Working Backwards), product strategy \u0026 outcome thinking (vision, OKRs, NCTs, product-market fit), strategic roadmapping (Now-Next-Later, Opportunity Solution Trees, story mapping), first principles \u0026 systems thinking (decomposition, feedback loops, leverage points), strategic decision-making (Cynefin, pre-mortems, Red Teaming, decision matrices), and bridging strategy to execution (dual-track agile, strategic narratives, stakeholder alignment, North Star metrics).\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🌐 Faculty of Service Design \u0026 Systems — `service-design/`\nThe **orchestration faculty** — bridges individual touchpoints into coherent end-to-end services. Covers Service-Dominant Logic (goods vs service thinking, 5 axioms), service blueprinting (5-layer blueprint with AI actor lanes), journey \u0026 moment mapping (emotional arcs, moments of truth, pain point scoring), ecosystem \u0026 stakeholder architecture (actor maps, value exchange, dependency matrix), AI-human handoff design (confidence thresholds, warm transfer, escalation ladder), service prototyping (Wizard of Oz, desktop walkthrough, riskiest assumption), and service health metrics (SERVQUAL, CSAT, CES, AI service scorecards).\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### ⚙️ Faculty of Software Engineering — `software-engineering/`\nThe **engineering foundation** — clean code, SOLID principles, software architecture (monolith/microservices/event-driven), API design (REST/GraphQL/gRPC), GoF design patterns, testing strategies (unit/integration/E2E/TDD), refactoring \u0026 code review, and project structure with dependency injection.\n\n**9 Courses** | **Level: Beginner → Advanced**\n\n### 🐳 Faculty of DevOps \u0026 Infrastructure — `devops-infra/`\nThe **deployment layer** — Linux server fundamentals, Docker containerization, CI/CD pipelines (GitHub Actions), cloud deployment (AWS/GCP/Cloud Run), networking \u0026 proxies (DNS/nginx/TLS), monitoring \u0026 logging (Prometheus/Grafana), and infrastructure as code (Terraform).\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🗄️ Faculty of Database Management — `database-management/`\nThe **data layer** — relational design \u0026 normalization (1NF-3NF), SQL mastery (joins/window functions/CTEs), indexing \u0026 query optimization, database migrations, NoSQL (MongoDB/Redis/CAP theorem), data modeling patterns, and security \u0026 backup.\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🤖 Faculty of AI Integration \u0026 LLM Engineering — `ai-integration/`\nThe **AI engineering layer** — prompt engineering (few-shot/chain-of-thought/structured output), RAG architecture (retrieval/chunking/re-ranking), embeddings \u0026 vector search, LLM orchestration (function calling/agents/ReAct), evaluation \u0026 hallucination detection, AI safety \u0026 guardrails, and MCP tool integration.\n\n**10 Courses** | **Level: Beginner → Advanced**\n\n### 🔐 Faculty of Security \u0026 Application Defense — `security/`\nThe **security layer** — OWASP Top 10 \u0026 threat modeling (STRIDE), authentication \u0026 authorization (OAuth/JWT/bcrypt/RBAC), API \u0026 input security (validation/SQL injection/rate limiting/CORS), encryption \u0026 data protection (TLS/AES/secrets management), secure SDLC \u0026 dependency security (SAST/DAST/npm audit), AI-specific security (prompt injection/jailbreaking), and incident response \u0026 compliance (GDPR/SOC2/post-mortem).\n\n**9 Courses** | **Level: Beginner → Advanced**\n\n### ⚡ Faculty of Performance Engineering — `performance/`\nThe **optimization layer** — Core Web Vitals \u0026 frontend performance (LCP/INP/CLS/Lighthouse), caching strategies (Redis/CDN/cache invalidation), backend optimization (N+1/connection pooling/async processing), database performance (EXPLAIN/indexes/cursor pagination), network \u0026 asset optimization (WebP/lazy loading/Brotli/HTTP/2), load testing \u0026 profiling (k6/flamegraph/P95), and performance budgets \u0026 CI enforcement.\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🧪 Faculty of Testing \u0026 Quality Assurance — `testing-qa/`\nThe **quality layer** — testing fundamentals \u0026 pyramid (TDD/BDD/isolation), unit \u0026 component testing (Jest/Vitest/mocking), integration \u0026 API testing (Supertest/test databases), E2E \u0026 UI testing (Playwright/Cypress/visual regression), performance \u0026 load testing (k6/stress/soak), CI/CD test automation (flaky tests/parallelization), and quality metrics \u0026 strategy (coverage/mutation testing/bug escape rate).\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🖥️ Faculty of Developer Experience — `dx/`\nThe **developer-facing layer** — DX fundamentals \u0026 strategy (empathy for devs, friction logging, DevEx framework), CLI design patterns (--help, exit codes, subcommands, progress bars), API design for developers (REST/GraphQL/gRPC ergonomics, error codes, SDK generation), documentation architecture (Diátaxis framework, docs-as-code, OpenAPI, MDX), SDK \u0026 library design (naming conventions, tree-shaking, middleware patterns), error messages for developers (actionable errors, structured logging, debugging tooling), and developer onboarding \u0026 metrics (TTFC/Time to First Call, DevEx surveys, DORA metrics).\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🗂️ Faculty of Information Architecture — `ia/`\nThe **structure layer** — IA fundamentals \u0026 organization schemes (LATCH: Location/Alphabet/Time/Category/Hierarchy), navigation \u0026 wayfinding (breadcrumbs, sitemaps, progressive disclosure, contextual nav), search systems (faceted search, autocomplete, relevance ranking, federated search), taxonomies \u0026 ontologies (controlled vocabularies, polyhierarchies, SKOS, knowledge graphs), content modeling \u0026 metadata (schema.org, Dublin Core, headless CMS, structured content), card sorting \u0026 tree testing (open/closed card sort, treejack, IA validation), and IA for AI \u0026 personalization (dynamic IA, recommendation engines, semantic search).\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n### 🤖 Faculty of Agentic Engineering \u0026 Orchestration — `agentic-engineering/`\nThe **operational layer** for autonomous AI agents — teaches how to *run agents in production*, beyond building single agents. Covers durable runtimes \u0026 control planes (state machines, checkpointing, HITL gates), context engineering (attention budget, compaction, JIT retrieval, scratchpads), multi-agent coordination (supervisor/worker, hierarchical, peer swarm, handoff protocols, delegation drift prevention), agent observability \u0026 evaluation (tracing, nested spans, trajectory eval, CI eval gates), cost-aware planning (model routing, confidence escalation, semantic caching, per-task budgets), agent safety \u0026 sandboxing (tool scoping, E2B microVMs, tool poisoning defense, audit trails), and agent productionization \u0026 lifecycle (versioning behavior bundles, non-human identity, canary/blue-green deployment, behavioral regression testing). Distinct from `ai-integration/` which covers *building* single agents (prompts, RAG, orchestration, eval, safety, MCP).\n\n**9 Courses** | **Level: Beginner → Advanced**\n\n### 🔬 Faculty of UX Research \u0026 Discovery — `ux-research/`\nThe **evidence layer** — teaches how to systematically gather, validate, and synthesize user evidence before designing. While other faculties teach *how to design* (Color, Typography, Layout) and *how to build* (Engineering, DevOps), this faculty teaches **how to research** — the foundation that precedes all design and product work. Covers research fundamentals \u0026 method selection (qualitative, quantitative, generative, evaluative, triangulation), qualitative interview techniques (semi-structured interviews, contextual inquiry, active listening, bias avoidance), quantitative methods (survey design, web analytics, A/B testing, usability metrics like SUS/NPS), research synthesis \u0026 sensemaking (affinity mapping, coding, journey mapping, persona development, insight statements), research operations (ResearchOps maturity, participant management, repositories, democratization, continuous discovery), usability testing \u0026 evaluation (moderated/unmoderated testing, task design, severity rating, heuristic evaluation), and AI-augmented research frontier (AI-moderated interviews, synthetic users, continuous discovery pipelines, AI insight validation, research ethics). Distinct from `ux-psikologi` (psychology of users) and `strategic-design` (problem framing) — this faculty teaches the *research methodology* itself.\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n---\n\n### ⚖️ Faculty of Design Ethics — `design-ethics/`\nThe **ethics layer** — teaches how to design responsibly. Covers ethical frameworks for designers (utilitarianism, deontology, virtue ethics, care ethics), privacy-first design (PbD principles, GDPR, data minimization, consent UX), inclusive design beyond accessibility (intersectionality, cognitive inclusion, economic and cultural inclusion), AI ethics \u0026 algorithmic fairness (bias types, fairness metrics, explainability, AI impact assessments), dark patterns \u0026 deceptive design (classification, detection, regulation, ethical persuasion alternatives), sustainability in digital design (carbon-aware UX, green hosting, lifecycle thinking, circular design), and ethical decision-making in organizations (ethics boards, red-teaming, ethical maturity models, whistleblowing).\n\n**7 Courses** | **Level: Beginner → Advanced**\n\n---\n\n## 🔮 Roadmap\n\n- [x] **ROADMAP v2 COMPLETE 🏁** — 216 courses, 29 faculties, 10 MCP tools\n- [ ] **v3 planning** — Submit your ideas!\n\n---\n\n\u003e *\"Deep knowledge makes agents truly powerful.\"* — Mas Aul 🔥\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkandarlubis31%2Ficil","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkandarlubis31%2Ficil","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkandarlubis31%2Ficil/lists"}