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Found 13,656 Skills
Route and carry out work on coding-agent skills across shunk031/skills and shunk031/skills-private. Use when asked to add, edit, rename, split, or remove a skill; when deciding which repository owns one; when writing or converting eval and trigger cases; or when a skill change has to reach a machine through the dotfiles subscription. Also use when a request names a skill while you are working in a dotfiles repository, because skill content no longer lives there.
Build MCP (Model Context Protocol) servers including tool definition, schema design, authentication, error handling, and Claude Code integration. Use this skill when the user needs to create an MCP server, expose APIs or databases to AI agents, design tool schemas, or integrate with Claude Code — even if they say 'build an MCP server', 'connect Claude to our database', 'expose our API to AI', or 'create a tool for Claude Code'.
Initialize a new Ruflo project with MCP tools, hooks, and agent configuration
Route tasks to optimal agents using learned patterns, model recommendations, and confidence scoring
One-click contribution flow for Open Design (nexu-io/open-design) — even for non-coders. Pick one of four cards (ship a Skill or Design System you made with OD; translate docs; fix a typo / write a blog; report a bug), the agent validates and opens a PR (or issue) for you. Trigger words contribute to open design, ship my OD skill, ship my OD design system, translate OD docs, report an OD bug, od-contribute.
Use when looking for a CLI, API wrapper, scraper, data-source tool, automation tool, or focused agent skill for a task; searches the Printing Press Library and installs matching tools.
Adversarial senior-engineer review for agent-generated plans, designs, and architectures. Treats the current output as junior work, constructs a senior reviewer whose domain expertise comes from live codebase research plus web research of current best practices, diagnoses altitude failures (too vague or too granular), then rewrites the plan into a scoped, state-of-the-art version. Use when the user says "junior to senior", "senior review", "review this like a staff engineer", when a plan feels hand-wavy or lost in details, or before committing to any agent-written plan.
Audit, prune, and improve agent guidance markdown files in repositories. Use when the user asks to check, audit, update, improve, or fix AGENTS.md, CLAUDE.md, or related guidance files. Adds missing commands and gotchas, removes stale entries, deduplicates, and keeps the file small and relevant. Scan for guidance files, evaluate quality against templates, output a quality report, then make targeted updates.
Add persistent, structured long-term memory to AI agents using Maximem Synap. Use this skill whenever the user is building, debugging, or evaluating an AI agent and mentions any of: "memory", "long-term memory", "persistent memory", "agent memory", "remember across sessions", "context window", "agent forgets", "user preferences", "personalization", "RAG over conversations", "multi-tenant memory", "memory layer", "Mem0", "Zep", "Letta", "SuperMemory", "Cognee", or asks how to integrate memory into LangChain, LangGraph, LlamaIndex, OpenAI Agents SDK, Pydantic AI, CrewAI, AutoGen, Google ADK, Haystack, Agno, Semantic Kernel, Microsoft Agent Framework, NVIDIA NeMo, LiveKit, Pipecat, Claude Agent SDK, Mastra, Vercel AI SDK, or MCP (no-code). Also trigger on direct mentions of "Synap", "Maximem", "maximem-synap", or `synap-*` package names. Covers SDK setup, scoping (User/Customer/Client), ingestion, retrieval, and one drop-in package per framework.
Use this skill when the user wants to analyze an existing pipe for improvement opportunities — automation gaps, manual bottlenecks, missing AI agents, field conditions, or adjacent processes. Acts as a process analyst: investigates, diagnoses, and improves the pipe in progressive rounds — each round delivers visible results.
Use when analyzing an existing TypeScript or JavaScript codebase to decide where and how to introduce Inngest. Covers repository discovery, framework and package detection, finding durability gaps in HTTP handlers, webhooks, cron jobs, queues, long-running jobs, AI agents, Agent Evals, polling loops, eval loops, and side-effect-heavy code, then producing and implementing an incremental integration plan.
Three-axis review of a diff against a fixed point: Standards (does it follow this repo's coding standards?), Spec (does it match the originating issue/PRD?), and Stability (were the spec's property-based tests shipped?). Runs axes as parallel sub-agents.