By haJ1t
AI/ML engineering: RAG system design, embeddings and vector search, dataset curation, model evaluation, and prompt engineering. Use when building RAG, embeddings, ML datasets, model evals, or LLM prompts.
Dataset creation, cleaning, augmentation, versioning, QA for ML/AI pipelines. Use when preparing or improving a training or evaluation dataset.
Embedding generation, vector storage, similarity search optimization, and embedding model selection. Use when building or tuning embedding pipelines.
Systematic LLM and ML model evaluation — benchmarks, metrics, regression detection, and model comparison. Use when assessing or comparing AI model quality.
Systematic prompt design, optimization, and evaluation framework for LLM applications. Use when crafting or improving prompts for AI systems.
End-to-end RAG system design — chunking strategies, embedding selection, retrieval optimization, reranking. Use when building or tuning a RAG pipeline.
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npx claudepluginhub haj1t/senior-dev-squad-skills --plugin ai-ml-eng-proSmart contracts, dApps, DeFi, NFT, testing, security, gas optimization. Use when building or auditing Web3 or blockchain projects.
ETL pipelines, data warehousing, streaming, orchestration, quality, governance. Use when designing or reviewing data pipelines.
LLM security: prompt injection, guardrails, PII redaction, model access control, audit. Use when securing AI apps or auditing LLM pipelines.
ML workflows, training pipelines, model evaluation, deployment, experiment tracking. Use when building or reviewing ML systems.
Supabase auth, RLS, realtime, storage, edge functions, database design. Use when building or reviewing Supabase-backed applications.
Give your AI a memory — mine projects and conversations into a searchable palace. 33 MCP tools, auto-save hooks, and guided setup.
Open-source, local-first Claude Code plugin for token reduction, context compression, and cost optimization using hybrid RAG retrieval (BM25 + vector search), reranking, AST-aware chunking, and compact context packets.
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
A growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.
Intelligent draw.io diagramming plugin with AI-powered diagram generation, multi-platform embedding (GitHub, Confluence, Azure DevOps, Notion, Teams, Harness), conditional formatting, live data binding, and MCP server integration for programmatic diagram creation and management.
Persistent file-based planning for AI coding agents. Crash-proof markdown plans (task_plan.md, findings.md, progress.md) that survive context loss and /clear, with an opt-in completion gate and multi-agent shared state. Manus-style. Works with Claude Code, Codex CLI, Cursor, Kiro, OpenCode and 60+ agents via the SKILL.md standard. Includes Arabic, German, Spanish, and Chinese (Simplified and Traditional).