ai-llm-inference
openbooklet.com/s/ai-llm-inferenceopenbooklet.com/s/ai-llm-inference@1.0.0GET /api/v1/skills/ai-llm-inferenceLLM inference patterns â latency budgeting, caching, batching, quantization, and parallelism. Use when optimizing serving cost or tail latency.
Event-driven hooks for AI coding agents. Use when automating Claude Code or Codex CLI with stdin JSON and decision-control responses.
Configure and build MCP servers for AI agent tool integration. Use when connecting Claude Code or Codex to databases, APIs, or custom tools.
Configure CLAUDE.md/AGENTS.md/CODEX.md for persistent agent context. Use when setting coding standards or architecture docs for a codebase.
Reference for creating AI agent skills with SKILL.md structure. Use when building or improving modular skill files for Claude Code or Codex.
Create AI coding agent subagents with YAML frontmatter and least-privilege tools. Use when designing delegation, tool selection, or safety rules.
Coordinate parallel subagents in dependency-aware waves. Use when executing multi-task plans with Claude Code or Codex agent swarms.
Measure what matters when adopting AI coding tools. This skill provides metrics frameworks, measurement methodology, ROI models, and reporting templates for engineering managers, VPs of Engineering, and CTOs evaluating or scaling AI coding agents.
Production AI agent patterns covering MCP, RAG, guardrails, observability, and ROI. Use when designing or evaluating agent systems.
ML and data science workflows â EDA, feature engineering, modelling, evaluation, and production handoff. Use when exploring data or building models.
Time series forecasting â LightGBM, Transformers, temporal validation, feature engineering, and production deployment. Use when building TS models.
Production MLOps covering CI/CD, serving, drift monitoring, and GenAI security. Use when deploying or operating ML and LLM systems in production.
Prompt engineering for production LLMs â structured outputs, RAG, tool workflows, and safety. Use when designing or debugging prompts for LLM APIs.
Data lake and lakehouse patterns: ingestion, CDC, Iceberg/Delta/Hudi, Trino/DuckDB, orchestration, and governance. Self-hosted and cloud.
Metabase REST API automation: auth, export/upsert cards and dashboards, visualization_settings. Use when scripting Metabase via API.
REST/GraphQL/gRPC/tRPC API design patterns. Use when designing APIs, writing OpenAPI specs, versioning, auth, or rate limiting.
Context-driven AI development with Claude Code and Codex. Use when transitioning teams to AGENTS.md workflows or multi-repo AI setups.
Generates conventional commit messages from git diffs. Use when you need well-formatted commit messages following Conventional Commits.
Team Git patterns for branching, PRs, commits, and code review. Use when choosing a branching model or hardening repo collaboration.
Structured dev workflows via /brainstorm, /write-plan, /execute-plan. Use when breaking down complex projects into systematic steps.
Writes PRDs and specs optimized for coding assistants. Use when authoring requirements or project context for Claude Code, Cursor, or Copilot.
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