Packs
12 packs@mesteriis
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
Agents from Intense-Visions/harness-engineering.
100 skills · pack
@fradser
Mattpocock
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
@alunadev
Ald Skills
Adrian Luna Díaz personal skill library — product management, engineering, design, and operations skills.
57 skills · pack
@matteobortolazzo
Flow
cenci workflow layer: portable engineering conventions and Claude Code's gated GitHub ticket-to-PR pipeline
27 skills · pack
@samyakjhaveri
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
Engineering
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
Pwdev Uiux
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
@samyakjhaveri
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”
8 skillsai-product
Guides building production-grade AI features with LLM integration patterns, RAG architecture, prompt engineering, and cost optimization.
42.4k
llm-ops
Guides production AI systems: RAG pipelines, embeddings, vector databases, fine-tuning, prompt engineering, cost estimation, quality evals, and caching.
2
llm-ops
Guides production LLM operations: RAG pipelines, embeddings, vector databases, fine-tuning, prompt engineering, cost estimation, quality evals, and AI architectures.
0 · bundle
More results
llm-ops
Implements production LLM operations: RAG pipelines, embeddings, vector databases, fine-tuning, advanced prompt engineering, cost estimation, quality evals, semantic caching, streaming, and agents.
3
ai-engineer
Build production-ready LLM applications, RAG systems, and intelligent agents with architecture design, model selection, and cost controls.
6
ai-engineer
Build production-ready LLM applications, advanced RAG systems, and intelligent agents with vector search, multimodal AI, and enterprise integrations.
42.4k
llm-ops
Provides guidance on production AI operations including RAG pipelines, vector databases, embeddings, fine-tuning, prompt engineering, cost estimation, and quality evaluation.
5
llm-ops
Provides guidance and code for production AI workflows including RAG pipelines, vector databases, embedding indexing, prompt engineering, cost estimation, semantic caching, and quality evaluation.
42.4k