Loading...
Loading...
Found 3,827 Skills
Ultimate 25+ years expert-level backend skill covering FastAPI, Express, Node.js, Next.js with TypeScript. Includes ALL databases (PostgreSQL, MongoDB, Redis, Elasticsearch), ALL features (REST, GraphQL, WebSockets, gRPC, Message Queues), comprehensive security hardening (XSS, CSRF, SQL injection, authentication, authorization, rate limiting), complete performance optimization (caching, database tuning, load balancing), ALL deployment strategies (Docker, Kubernetes, CI/CD), advanced patterns (microservices, event-driven, saga, CQRS), ALL use cases (e-commerce, SaaS, real-time, high-traffic), complete testing (unit, integration, E2E, load, security). Route protection, middleware, authentication implementation in PERFECTION. Use for ANY backend system requiring enterprise-grade security, performance, scalability, and architectural excellence.
Transform Obsidian video notes from the Vault into published notes on joelclaw.com. Use when publishing video notes, converting vault video content to the site, or when asked to 'publish a video note,' 'turn this video into a note,' 'publish from vault/videos,' or any task involving /Vault/Resources/videos → joelclaw content. Triggers on references to video notes, vault video files, or publishing video content to the blog.
Use when users want to define, codify, or update their brand identity and connect it to design systems. Produces a self-contained user-level skill at ~/.claude/skills/{brand-slug}/SKILL.md that enforces brand guidelines whenever visual assets or written content are created.
This skill should be used when the user asks to "check for non-repudiation privacy risks", "analyze excessive audit logging", "find privacy issues related to accountability", "check for forced identity linking", or mentions "non-repudiation" in a privacy context. Maps to LINDDUN category N. This is the INVERSE of STRIDE repudiation -- here too much proof is the threat.
A fiscally disciplined finance leader who monitors provider spend, forecasts burn against budget, and enforces cost controls.
Whole-codebase vulnerability analysis leveraging 1M context window. Loads entire project source, runs deep security analysis in a single pass. Opus 4.6 found 500 zero-day vulnerabilities in pre-release testing — this skill weaponizes that capability.
Track data lineage and provenance from source to consumption. Use when auditing data flows, debugging data quality issues, ensuring compliance (GDPR, SOX), or understanding data dependencies. Covers lineage tracking, impact analysis, data catalogs, and metadata management.
Check an IP address across multiple public geolocation and reputation sources and return a best-matched location summary.
Used to audit codebases to ensure their naming complies with established terminology and specifications. This Skill should be used when you need to enforce a project's 'Ubiquitous Language', identify deviations in method/variable/parameter naming, and propose modification suggestions.
Style, review, and refactoring standards for Bash shell scripting. Trigger when `.sh` files, files with `#!/usr/bin/env bash` or `#!/bin/bash`, or CI workflow blocks with `shell: bash` are created, modified, or reviewed and Bash-specific quality controls (quoting safety, error handling, portability, readability) must be enforced. Do not use for generic POSIX `sh`, PowerShell, or language-specific application style rules. In multi-language pull requests, run together with other applicable `*-style-guide` skills.
Model Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
Multi-AI Parallel Deep Research. Triggered when users need comprehensive research, in-depth study, multi-party comparison, or comprehensive analysis covering multiple dimensions and sources for a certain topic. Suitable for complex topics (technical selection, competitor analysis, industry trends, controversial topics, etc.), not suitable for simple fact queries. Conduct parallel research through multiple AI services, cross-validate, and output a comprehensive report with citations.