ai-engineeringlisted

Reviews and guides LLM/AI application engineering: prompt design, prompt caching, multimodal inputs, RAG, agent loops and tool design, resilience (rate limits, retries, fallbacks), memory, model migration, evals, testing, prompt-injection defence, and observability. Synthesises practices from Anthropic, OpenAI, Google, OWASP LLM Top 10, and practitioners (Hamel Husain, Eugene Yan, Chip Huyen). Triggers on "review my prompt", "design a system prompt", "optimise tokens", "set up RAG", "build an agent", "handle rate limits", "migrate to a new model", "write evals", "test my prompt", "audit AI code", "/ai-engineering".
mthines/agent-skills · ★ 5 · AI & Automation · score 83

Install: claude install-skill mthines/agent-skills

# AI Engineering Prescriptive guidance for building and reviewing LLM/AI applications. Thirteen orthogonal concerns — load only the rules the current task needs. > **This `SKILL.md` is a thin index.** Detailed rules live in > `rules/*.md` and load on demand. > Curated source URLs live in `references/primary-sources.md`. > Date-flagged changes since 2024 live in `references/recent-changes.md`. > Literal scaffolding lives in `templates/`. --- ## Mode Detection Parse `$ARGUMENTS` (first token) and detect the mode: | Mode | Default | Trigger | | ---------- | ------- | ----------------------------------------------------------------------------- | | `guide` | **yes** | Default. Open question ("how should I …", "what's the best way to …"). | | `review` | | `$0 == "review"`, or a file/path is supplied as `$ARGUMENTS`. | | `design` | | `$0 == "design"`, or "scaffold a prompt / system prompt / eval". | State the detected mode and the area(s) in scope before continuing: ``` Mode: review Areas: prompt-writing, system-prompt-design Targets: src/agents/triage.ts (system prompt at L24-78) ``` --- ## Area Routing Map the user's request to one or more rule files. Load **only** the rules listed for the matched area(s). | Area | Rule file | Load when