Packs

12 packs

Engineering Bible AI

Engineering Bible AI from Mesteriis/Engineering-Bible-AI.

60 skills · pack

@muratcankoylan

Agent Skills For Context Engineering

Agent Skills For Context Engineering from muratcankoylan/Agent-Skills-for-Context-Engineering.

16 skills · pack

@intense-visions

Agents from Intense-Visions/harness-engineering.

100 skills · pack

BDD-first engineering skills forked from mattpocock/skills v1.2.3

43 skills · pack

@alirezarezvani

Engineering Team

32 engineering skills: architecture, frontend, backend, fullstack, QA, DevOps, security, AI/ML, data engineering, Playwright (9 sub-skills), self-improving agent, Stripe integration, TDD guide, tech stack evaluator, Google Workspace CLI, a11y audit (WCAG 2.2), Azure cloud architect, GCP cloud architect, security pen testing, Snowflake development, adversarial-reviewer, ai-security, cloud-security,

16 skills · pack

Adrian Luna Díaz personal skill library — product management, engineering, design, and operations skills.

57 skills · pack

@matteobortolazzo

cenci workflow layer: portable engineering conventions and Claude Code's gated GitHub ticket-to-PR pipeline

27 skills · pack

Pocock Engineering

Engineering workflow skills from Matt Pocock's skills repo (triage, to-issues, to-prd, tdd, prototype, diagnose, grill-with-docs, improve-codebase-architecture, zoom-out). Covers issue lifecycle, TDD, prototyping, architectural review, domain grilling, and PRD generation. NOT for: daily development workflow — install individual skills as needed.

7 skills · pack

@alirezarezvani

37 advanced engineering skills: agent designer, agent workflow designer, RAG architect, database designer + schema designer + SQL assistant, migration architect, observability designer, dependency auditor, changelog generator (with semantic version bumper and hotfix/rollback procedures), API design reviewer, API test suite builder, CI/CD pipeline builder, MCP server builder, skill security auditor

33 skills · pack

@pwdev-solucoes

Stack-agnostic UI/UX engineering v2.0 — 6 real subagents, 5-phase workflow with gates, Figma integration, WCAG 2.1 AA, audit hooks

10 skills · pack

@alirezarezvani

C Level Advisor

33 C-level advisory skills + c-level-agents plugin layer: virtual board of directors (CEO, CTO, COO, CPO, CMO, CFO, CRO, CISO, CHRO) plus General Counsel, CDO, CAIO, CCO, and VP of Engineering (DORA delivery throughput analyzer, engineering hiring funnel calculator with conversion + pipeline gap, eng team structure designer with squad/tribe + manager-trigger), executive mentor, founder coach, orch

27 skills · pack

Business Process

Business process skills (process-optimizer, sop-writer, workflow-mapper, weekly-review). Useful for operational documentation, SOP generation, and workflow analysis. NOT for: software engineering tasks — these target organizational processes, not code.

4 skills · pack

Results for “engineering”

29 skills

context-engineering

Optimizes agent context setup by structuring rules, specs, source files, error output, and conversation history to improve output quality.

prompt-engineering

Learn and apply prompt engineering techniques for LLMs, image generators, and video models using the inference.sh CLI.

context-engineering-advisor

Diagnose whether an AI workflow suffers from context stuffing or benefits from context engineering, and apply structured techniques to improve reliability.

context-fundamentals

Explains foundational concepts of context engineering: what context is, attention mechanics, the U-shaped attention curve, and why context quality matters more than quantity.

16.9k · bundle

Guides building production-grade AI features with LLM integration patterns, RAG architecture, prompt engineering, and cost optimization.

nimoqup046-collab

Guides production AI systems: RAG pipelines, embeddings, vector databases, fine-tuning, prompt engineering, cost estimation, quality evals, and caching.

More results

Guides production LLM operations: RAG pipelines, embeddings, vector databases, fine-tuning, prompt engineering, cost estimation, quality evals, and AI architectures.

Discovers and applies curated prompts from the prompts.chat collection to optimize AI interactions, prompt engineering, and workflow integration.

Implements production LLM operations: RAG pipelines, embeddings, vector databases, fine-tuning, advanced prompt engineering, cost estimation, quality evals, semantic caching, streaming, and agents.

ai-prompt-engineering-safety-review

Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness, providing detailed improvement recommendations with frameworks, testing methodologies, and educational content.

ai-engineering-standards

Enforces production-grade Python and AI engineering standards for FastAPI, LangChain/LangGraph, RAG pipelines, and LLM integrations, covering type safety, error handling, testing, and security.

Forces one deeper, more creative pass on an answer or plan while preserving the original escalation prompt verbatim.

prompt-optimizer

Creates, optimizes, and iteratively refines agent prompts, system prompts, developer prompts, and reusable prompt templates with evals.

muapi-nano-banana

Generates high-fidelity images using reasoning-driven prompts and structured creative briefs via muapi.ai.

Estrutura prompts para geradores de imagem e vídeo, otimizando custo e consistência com a marca.

Forces a second, harder escalation pass using the original glazer prompt words verbatim, pushing for a sharper replacement thesis rather than more polish.

prompt-engineer

Designs, optimizes, and evaluates prompts for LLMs, including structured outputs, chain-of-thought, and evaluation frameworks.

10.4k · bundle

Build production-ready LLM applications, advanced RAG systems, and intelligent agents with vector search, multimodal AI, and enterprise integrations.

Generates images from text prompts using diffusion models, covering prompt engineering, inpainting/outpainting, ControlNet, and API integration for production workflows.

prompt-engineer

Designs and optimizes prompts for LLM-powered applications, covering system prompt architecture, context management, output formatting, and evaluation.

ai-ml-technologies

Covers AI, machine learning, LLMs, prompt engineering, and blockchain development with code examples and best practices for building AI applications and smart contracts.

lucaspmarie-a11y

Provides guidance on production AI operations including RAG pipelines, vector databases, embeddings, fine-tuning, prompt engineering, cost estimation, and quality evaluation.

Rewrites free-form draft prompts into the conventions Claude Opus 4.6 or 4.8 responds best to, either inline or by overwriting a draft file.

Provides guidance and code for production AI workflows including RAG pipelines, vector databases, embedding indexing, prompt engineering, cost estimation, semantic caching, and quality evaluation.

sakamoto-family-smile

prompt-optimizer

Analyzes draft prompts, identifies intent and gaps, matches ECC components, and outputs an optimized prompt for the user to paste and run. Advisory only, never executes the task.

context-degradation

Diagnose and mitigate context degradation patterns including lost-in-middle failures, context poisoning, distraction, confusion, and clash in AI agent systems.

16.9k · bundle

Define every visual attribute as structured VGL JSON for deterministic, reproducible image generation with Bria FIBO models, covering objects, lighting, camera settings, composition, and style.

video-prompting-guide

Learn best practices for writing effective AI video generation prompts, covering shot types, camera movements, lighting, style keywords, and model-specific tips for Veo, Seedance, Wan, Grok, and others.

Generates and edits images using GPT Image 2 across three modes: direct generation via OpenAI-compatible API, prompt engineering for host-native image tools, or pure prompt advisory. Includes 80+ structured templates for posters, UI mockups, product visuals, maps, slides, and more.