skills/payload-cms/SKILL.md
Payload CMS — open-source headless CMS and app framework built on Next.js with TypeScript. MANDATORY TRIGGERS: payload, payload-cms, payloadcms, payload cms, headless cms nextjs. Also trigger when building content management systems with Next.js, configuring CMS collections/fields/hooks, or implementing admin panels with TypeScript. When in doubt about whether to use this skill for CMS or content modeling tasks, use it.
npx skillsauth add abhisheksharma-17/skills-graph payload-cmsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Version tracked: 3.82.x | Source: https://payloadcms.com/docs
| File | Read When | |------|-----------| | 00-overview | Starting with Payload, installation, core concepts, project structure | | 01-collections | Defining collections, document schemas, CRUD config | | 02-fields | Field types, validation, conditional logic, field-level config | | 03-globals | Singleton data like site settings, nav, footers | | 04-access-control | Function-based access control, RBAC patterns, field-level | | 05-hooks | Lifecycle hooks for collections, globals, and fields | | 06-authentication | Auth strategies, JWT, API keys, email/password, custom | | 07-apis | Local API, REST API, GraphQL — querying and mutations | | 08-admin-panel | Admin customization, custom components, live preview | | 09-database-adapters | Postgres, MongoDB, SQLite — adapter config and migrations | | 10-rich-text-lexical | Lexical editor, features, custom nodes, serialization | | 11-plugins | Official plugins — SEO, forms, search, cloud storage, nested docs | | 12-versions-drafts | Version history, drafts, autosave, publishing workflows |
npx create-payload-app@latest my-project
# or add to existing Next.js app
npm install payload @payloadcms/next @payloadcms/richtext-lexical
development
High-throughput LLM inference and serving engine with PagedAttention, continuous batching, and OpenAI-compatible API. MANDATORY TRIGGERS: vLLM, vllm, LLM serving, LLM inference engine, PagedAttention. Also trigger when the user wants to serve LLMs in production, deploy models with tensor parallelism, use speculative decoding, quantize models for inference, build OpenAI-compatible API servers, or optimize LLM throughput and latency. When in doubt about whether to use this skill for LLM serving tasks, use it.
tools
Type-safe Python agent framework for building production-grade GenAI applications with Pydantic validation, structured outputs, and dependency injection. MANDATORY TRIGGERS: pydantic-ai, pydantic_ai, PydanticAI, pydantic ai agent. Also trigger when the user wants to build type-safe AI agents in Python, create structured LLM outputs with Pydantic models, implement dependency injection for agents, use tools/capabilities with LLMs, or build multi-agent systems with Python type safety. When in doubt about whether to use this skill for Python AI agent tasks, use it.
development
Durable execution platform for building fault-tolerant workflows, long-running processes, and resilient distributed applications. MANDATORY TRIGGERS: temporal, temporal.io, temporalio, durable execution, workflow orchestration engine. Also trigger when the user wants to build fault-tolerant workflows, implement saga patterns, create long-running distributed processes, orchestrate microservices with retries and timeouts, or build durable AI agent pipelines. When in doubt about whether to use this skill for workflow orchestration or durable execution tasks, use it.
tools
AI framework for building RAG pipelines, agents, workflows, and data-augmented LLM applications with 300+ integrations. MANDATORY TRIGGERS: llamaindex, llama-index, llama_index, LlamaIndex, VectorStoreIndex, SimpleDirectoryReader, LlamaHub, LlamaParse. Also trigger when the user wants to build RAG applications with LlamaIndex, create document indexing pipelines, build agentic workflows with tool calling, implement structured data extraction from documents, or connect LLMs to custom data sources. When in doubt about whether to use this skill for RAG, document indexing, or LLM data augmentation tasks, use it.