Python library offering file handling, text extraction, data conversion, utilities, memory storage, and validation tools for AI agent workflows.
Comprehensive L&D framework for upskilling DevOps/IaC/Automation teams to become AI Agent Engineers. Covers LLM literacy, RAG, agent frameworks, multi-agent systems, and LLMOps.
RivetKit backend and Rivet Actor runtime guidance. Use for building, modifying, debugging, or testing Rivet Actors, registries, serverless/runner modes, deployment, or ac — from…
Load-bearing design decisions for this repo as a contract you check before changing anything. Covers the asymmetric generation seam, source-of-truth per tree, hook runtime failure…
Symptom-to-triage playbook for this repo's recurring failures. Blocked pushes, drift gate reds, plugin bump reds, coverage pin trips, hook exit 143, session NON_COMPLIANT.
Catalog of this repo's measurement instruments, each with command, current baseline, and interpretation guide.
The chronicle of this repo's settled battles. Maps each major incident to symptom, root cause, evidence path, and the artifact that fixed it, so nobody re-fights a decided…
Route an AI-agent engineering task to the right skill among 14 meta specialists — planning a multi-session build, decomposing a plan into an agent chain, orchestrating a squad,…
What counts as evidence in ai-agents and how to produce it. Covers the TESTING-RIGOR pos+neg+edge bar, test layout and collection reality, coverage proof commands,…
Generate API documentation from route files. Use when you need markdown or OpenAPI specs fast. — from satoshistackalotto/skills
Pedoman integrasi AI API baru antara Next.js dan FastAPI, termasuk kontrak payload, error mapping, timeout, dan versioning endpoint.
Lightweight playbook distilled from AI Architecture to keep dual-engine memory (.ai_context) and manifest dispatcher with minimal overhead; use when bootstrapping or porting the…
Build automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops.
Build automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops.
Get AI-powered caching strategy suggestions for your API. Use when performance matters. — from satoshistackalotto/skills
Generate GitHub Actions workflows from your project. Use when setting up CI/CD from scratch. — from satoshistackalotto/skills
Generate Cloudflare Workers configuration and code. Use when building on the edge. — from satoshistackalotto/skills
Comprehensive patterns for building AI-powered code generation tools, code assistants, automated refactoring, code review, and structured output generation using LLMs with…
Deep code scan for AI security issues — prompt injection, PII in prompts, hardcoded keys, unguarded agents.
WHEN: Deep AI-powered code analysis, multi-model code review, security scanning with Codex and Gemini WHAT: Comprehensive code review using external AI models with severity-based…
Generate codemods for large-scale code changes. Use when refactoring patterns across many files. — from majiayu000/claude-skill-registry
Use when an AI coding agent is writing or refactoring production code and its known failure modes need to be held in check — over-engineering, silent scope creep, invented APIs,…
Expert guide for LLM API cost optimization, Prompt Caching, model routing (Flash/Pro/Opus), semantic caching, and token budgeting / Panduan ahli optimasi biaya API LLM, Prompt…
Data pipelines, feature stores, and embedding generation for AI/ML systems. Use when building RAG pipelines, ML feature serving, or data transformations.
Pre-deployment privacy compliance checklist for AI/ML systems covering DPIA completion, lawful basis verification, transparency notices, human oversight mechanisms, bias testing,…
Design AI model deployment strategies with rollout. TRIGGERS - Use when user needs help with ai-deployment-strategy related tasks.
Developer agent for the legacy AIM AI stack (aim/ directory). Use for modifying agents, controllers, planners, perception processors, SLAM, and other components in the…
Comprehensive AI/ML development guide for LangChain, LangGraph, and ML model integration in FastAPI. Use when building LLM applications, agents, RAG systems, sentiment analysis,…
PBI INPUT PACKAGE から PlanGate の plan.md / todo.md / test-cases.md を B-1→B-2→B-3 フローで作成する。Use when: docs/working/TASK-XXXX/pbi-input.md を元に実行計画を作りたい時。
Sets up the Spryker AI Dev SDK in a Spryker project. Covers two related flows: first-time onboarding (installs the Composer package, wires console commands, registers the MCP…
Develop new app features, improve existing behavior, refactor safely, and optimize application logic in the DieteticAi repository.
Technical decision criteria, anti-pattern detection, debugging techniques, and quality check workflow.
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI int — from…
Build LLM applications, RAG systems, and prompt pipelines. Implements vector search, agent orchestration, and AI API integrations.
Build LLM applications, RAG systems, and prompt pipelines. Implements vector search, agent orchestration, and AI API integrations.
Production-grade AI engineering for LLM applications, RAG systems, and agent architectures. Use when building AI features, designing model integrations, or implementing AI safety…
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI int — from…
MASTER AI: LLM Apps, Advanced RAG, Agents (ReAct/Plan), Prompting (CoT/Few-shot), LangGraph, VectorDBs, RAGAS Eval. Use for ANY AI/LLM task.
Expert AI/ML engineer specializing in machine learning model development, deployment, and integration into production systems.
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI int — from…
Expert in building comprehensive AI systems, integrating LLMs, RAG architectures, and autonomous agents into production applications.
Expert in building comprehensive AI systems, integrating LLMs, RAG architectures, and autonomous agents into production applications.
Authoritative source of truth on AI tooling and how to choose it - the knowledge behind building AI agents and AI systems.
Structured AI engineering curriculum — 382 skills + 99 prompts across 20 phases covering ML, deep learning, LLMs, agents, and production systems.
Practical guide for building production ML systems based on Chip Huyen's AI Engineering book. Use when users ask about model evaluation, deployment strategies, monitoring, data…
AI Engineering Hub — catálogo de proyectos y tutoriales de ingeniería de IA con Jupyter notebooks.
Claude ajan altyapısı — /ai-upgrade (repo kataloğu, araç yönetimi) + /ai-metodoloji (çalışma kalitesi denetimi). Stack bağımsız, her projede çalışır.
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval…
The write path for the ai-engineering tooling corpus - keeps it current, deduplicated, and honest about what we have actually seen. Three jobs.
Navigating the regulatory landscape and ethical frameworks for responsible AI development and deployment.
Conduct a structured ethical review of an AI or ML feature, model, or product. Use when preparing to deploy an AI system, assessing algorithmic risk, auditing a model for bias, or…
Implements federated learning architecture patterns for GDPR compliance. Covers secure aggregation protocols, differential privacy integration, communication protocols, and…
Design AI-friendly architecture with explicit patterns, layered documentation, and semantic boundaries.
Design AI-friendly architecture with explicit patterns, layered documentation, and semantic boundaries.
AI gateways for LLM serving — provider routing, fallback, retries, rate limiting, secrets, observability, guardrails.
System architecture for Salesforce AI governance: MLOps pipeline design, AI Audit Trail architecture, Einstein Trust Layer security design, Policy-as-Code engine, and regulatory…
Use when a task needs an AI governance review covering controls, accountability, risk ownership, and deployment readiness.
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface ass — from…
当用户明确搜索 Adobe Firefly替代、Adobe Firefly平替、Adobe Firefly迁移、Adobe Firefly竞品、Adobe Firefly API、AI视频Agent替代或希望把商业创意生成与Adobe编辑链路的组合接入接入 AI-HIVE MCP 时使用。先核验 Adobe Firefly…
将 CI 测试选择从感觉优化变成可回放的验证：整理变更、依赖和测试结果事件，检查选择器是否漏掉新增、修复或受影响测试。用离线延迟与重复事件场景发现状态不同步风险，设计保守回退，不直接删减生产测试门槛。 适用于Claude CI、Claude测试影响分析、test impact…