ai-engineering-toolkit
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
npx skills add majiayu000/claude-skill-registry --skill ai-engineering-toolkit --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# AI Engineering Toolkit ## Overview A collection of 6 structured, expert-level workflows that turn your AI coding assistant into a senior AI engineering partner. Each skill encodes a repeatable methodology — not just "ask AI to help," but a step-by-step decision framework with quantitative scoring, checklists, and decision trees. The key difference from ad-hoc AI assistance: **every workflow produces consistent, reproducible results** regardless of who runs it or when. You can use the scoring systems as team baselines and write them into CI/CD pipelines. ## When to Use This Skill - Use when evaluating or optimizing LLM system prompts before production deployment - Use when designing a RAG pipeline and need structured architecture decisions (not just boilerplate code) - Use when planning token budget allocation across context window zones - Use when running pre-launch security audits on AI agents - Use when building evaluation frameworks for LLM applications - Use when thinking through product strategy before writing code ## How It Works ### Skill 1: Prompt Evaluator Scores prompts across 8 dimensions (Clarity, Specificity, Completeness, Conciseness, Structure, Grounding, Safety, R
- Overview
- When to Use This Skill
- How It Works
- Skill 1: Prompt Evaluator
- Skill 2: Context Budget Planner
- Skill 3: RAG Pipeline Architect
- Skill 4: Agent Safety Guard
- Skill 5: Eval Harness Builder
- Skill 6: Product Sense Coach
- Examples
- Example 1: Prompt Evaluation
- Example 2: Security Audit
- Best Practices
- Security & Safety Notes
Via skill install command (Claude Code / WorkBuddy / Cursor) Manual git clone https://github.com/viliawang-pm/ai-engineering-toolkit.git cp -r ai-engineering-toolkit/skills/* ~/.claude/skills/
What does the ai-engineering-toolkit skill do?
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill ai-engineering-toolkit --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.