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alirezarezvani 2026-08-25 20:56:22 +00:00 committed by github-actions[bot]
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@ -3,7 +3,7 @@
"name": "claude-code-skills",
"description": "Production-ready skill packages for AI agents - Marketing, Engineering, Product, C-Level, PM, and RA/QM",
"repository": "https://github.com/alirezarezvani/claude-skills",
"total_skills": 362,
"total_skills": 363,
"skills": [
{
"name": "agent-launcher-orchestrator",
@ -1001,6 +1001,12 @@
"category": "engineering-advanced",
"description": "Use when the user asks to create ERD diagrams, normalize database schemas, design table relationships, or plan schema migrations."
},
{
"name": "deep-learning-book",
"source": "../../engineering/deep-learning-book/skills/deep-learning-book",
"category": "engineering-advanced",
"description": "Study companion and working knowledge base for the Deep Learning textbook by Goodfellow, Bengio & Courville (MIT Press, 2016), read free at deeplearningbook.org. Indexes all 20 chapters, carries a 2016-to-2026 delta layer naming what the book got right, what was superseded (transformers, AdamW, diffusion, double descent) and what still holds, and ships four deterministic tools: a prerequisite-aware reading-path planner, a training-failure diagnostic, a capacity-and-regularization planner, and a parameter/FLOP/activation-memory calculator. Use when studying or teaching this book, planning a route through it, deciding whether a chapter's advice is still current, or translating its math into a training decision. It points at the official chapters \u2014 it never reproduces them."
},
{
"name": "demo-video",
"source": "../../engineering/demo-video/skills/demo-video",
@ -1223,18 +1229,18 @@
"category": "engineering-advanced",
"description": "Use when the user asks to design a RAG pipeline, choose a chunking strategy or embedding model, pick a vector database, or evaluate retrieval quality (precision@k, recall@k, NDCG). Examples: 'design a RAG system for our docs', 'what chunk size should I use for this corpus', 'evaluate my retriever against ground truth'. NOT for general LLM cost tuning (use llm-cost-optimizer) or agent loops over retrieval (use agenthub)."
},
{
"name": "run",
"source": "../../engineering/autoresearch-agent/skills/run",
"category": "engineering-advanced",
"description": "Run a single experiment iteration. Edit the target file, evaluate, keep or discard. Use when the user runs /ar:run or asks for one manual autoresearch iteration."
},
{
"name": "run",
"source": "../../engineering/agenthub/skills/run",
"category": "engineering-advanced",
"description": "One-shot lifecycle command that chains init \u2192 baseline \u2192 spawn \u2192 eval \u2192 merge in a single invocation. Use when the user runs /hub:run or asks to execute a full AgentHub competition end-to-end."
},
{
"name": "run",
"source": "../../engineering/autoresearch-agent/skills/run",
"category": "engineering-advanced",
"description": "Run a single experiment iteration. Edit the target file, evaluate, keep or discard. Use when the user runs /ar:run or asks for one manual autoresearch iteration."
},
{
"name": "runbook-generator",
"source": "../../engineering/skills/runbook-generator",
@ -2220,7 +2226,7 @@
"description": "Software engineering and technical skills"
},
"engineering-advanced": {
"count": 90,
"count": 91,
"source": "../../engineering",
"description": "Advanced engineering skills - agents, RAG, MCP, CI/CD, databases, observability"
},

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../../engineering/deep-learning-book/skills/deep-learning-book