AI & LLM Engineering · By alirezarezvani

Behavioral guardrails for LLM-assisted coding. An agent skill from alirezarezvani/ClaudeForge.

alirezarezvani/ClaudeForge

Deep expertise in ML/CV model selection, training pipelines, and inference architecture.

alirezarezvani/claude-cto-team

A skill your agent uses when planning product experiments, writing testable hypotheses, estimating sample size, prioritizing tests, or interpreting A/B outcomes with practical statistical rigor.

alirezarezvani/claude-skills

Computer vision engineering skill for object detection, image segmentation, and visual AI systems.

alirezarezvani/claude-skills

A skill your agent uses when the user asks to optimize prompts, design prompt templates, evaluate LLM outputs with an eval set, measure RAG retrieval quality, validate agent/tool configurations…

alirezarezvani/claude-skills

Inter-agent communication protocol for C-suite agent teams. An agent skill from alirezarezvani/claude-skills.

alirezarezvani/claude-skills

Study companion and working knowledge base for the Deep Learning textbook by Goodfellow, Bengio & Courville (MIT Press, 2016), read free at deeplearningbook.org.

alirezarezvani/claude-skills

Chief AI Officer advisory for startups: model build-vs-buy decisions (API vs fine-tune vs in-house), AI risk classification under EU AI Act + US state patchwork, AI cost economics…

alirezarezvani/claude-skills

Turns marketing prompts into tested, versioned production assets: A/B prompt evaluation against structured test cases, immutable prompt version history with diffs, ready-to-use marketing prompt…

alirezarezvani/claude-skills

Orchestrate free opencode workers from Claude Code to cut token costs.

alirezarezvani/claude-skills

Discover, find, compare, audit, repair, adapt, and design repeatable AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs.

alirezarezvani/claude-skills

A skill your agent uses 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).

alirezarezvani/claude-skills

/cs:cross-eval <memo — Multi-model consensus on a board memo or strategy brief.

alirezarezvani/claude-skills

Evaluate and rank agent results by metric or LLM judge for an AgentHub session.

alirezarezvani/claude-skills

A skill your agent uses when managing prompts in production at scale: versioning prompts, running A/B tests on prompts, building prompt registries, preventing prompt regressions, or creating eval…

alirezarezvani/claude-skills

Knowledge base from "Spinning Up in Deep RL" by Joshua Achiam (OpenAI, MIT-licensed).

alirezarezvani/claude-skills

Use proactively whenever LLM API costs come up -- or should.

alirezarezvani/claude-skills