Universal link validation using lychee for Claude Code sessions. Runs at session end to detect broken links and path policy violations.

Comprehensive link checking and validation for documentation. Validate internal links, external URLs, anchors, detect redirects, monitor link rot, and generate sitemap validation reports.

link

This skill generates professional LinkedIn announcement text for intelligent textbooks by analyzing book metrics, chapter content, and learning resources to create engaging posts with key statistics, hashtags, and links to the published site. Use this skill when you need to create social media announcements about textbook completion or major milestones.

Esta skill deve ser usada quando o usuário solicitar candidaturas automáticas em vagas do LinkedIn relacionadas a Inteligência Artificial (IA) no Brasil, priorizando vagas com cadastro simplificado (Easy Apply). A skill filtra vagas por palavras-chave de IA, localização no Brasil, nível de senioridade (se especificado) e tipo de candidatura simplificada.

linkedin_job_resume_optimizer

Comprehensive LinkedIn personal branding analysis, profile optimization, and visibility improvement skill using Claude for Chrome browser tools. Use when users request LinkedIn profile analysis, personal branding audit, profile optimization recommendations, LinkedIn visibility improvement, headline optimization, About section review, content strategy guidance, engagement analysis, or Social Selling Index improvement. Works with Claude for Chrome to analyze profile photos, banners, headlines, About sections, experience, skills, recommendations, featured content, activity/posts, and network engagement directly from the user's browser.

linkedin-post-crafter

Create professional LinkedIn content and thought leadership posts that build authority

Generate LinkedIn profile update instructions by applying best practices to career data.

Create LinkedIn posts for lead generation and thought leadership. Use when projecting ideas to LinkedIn, creating post series, or reviewing LinkedIn content. Includes LinkedIn-specific voice (punchier, more personal), format rules, and weekly rhythm guidance.

Master LINQ and EF Core query optimization including N+1 prevention, eager loading, projections, and performance patterns. Use when: (1) fixing N+1 queries, (2) optimizing slow queries, (3) implementing efficient data access, (4) reducing database load.

An autonomous loop for the agent to identify, fix, and verify linting and formatting violations using [Trunk](https://trunk.io).

Checks code for linting issues and style compliance before commits

Iteratively run linters, apply auto-fixes, and resolve remaining issues using Trunk.

Expert assistant for analyzing and fixing linting and formatting issues in the KR92 Bible Voice project using Biome and TypeScript. Use when fixing lint errors, resolving TypeScript issues, applying code formatting, or reviewing code quality.

Detect and fix violations of project instructions defined in .claude/rules/. Use when checking code compliance, reviewing changes, or when the user asks about instruction violations.

lint-kb

Execute markdown validation with taxonomy-based classification and custom rules. Use when validating markdown compliance with LLM-facing writing standards or when generating structured validation reports.

Unified linting and auto-fix for Python (Ruff) and TypeScript (ESLint) in monorepo. Use when fixing lint errors, running pre-commit checks, or diagnosing persistent code quality issues. Orchestrates auto-fix first, then root-cause analysis.

lint-skill

Enforces validation pattern compliance across all agent profiles with automated detection and fixing

ring:linting-codebase

Generic linting workflow for multiple languages with auto-fix and error resolution guidance

Master essential Linux skills for penetration testing including navigation, file manipulation, text processing, networking, process management, permissions, and bash scripting. Linux is the preferred

iOS 26/macOS 26 Liquid Glass design system with complete API coverage. Use when user asks about iOS 26 design, Liquid Glass, glassEffect modifier, GlassEffectContainer, morphing animations, HIG compliance, visual styling, or the new Apple design language.

iOS 26 Liquid Glass expert. Use when user asks about Liquid Glass implementation, SwiftUI glassEffect, migration from iOS 17/18, morphing animations, GlassEffectContainer, or wants to generate glass-style UI components. Covers code generation, troubleshooting, HIG compliance, accessibility, performance optimization, and cross-platform differences.

Generate SwiftUI LiquidGlass components + tokens + accessibility + perf checks for iOS 26+/watchOS 26+.

Lisa - intelligent assistant for memory and tasks. Triggers on 'lisa', 'hey lisa', or addressing lisa directly.

Validate Lisp code (Clojure, Racket, Scheme, Common Lisp) for syntax errors, parenthesis balance, and semantic issues. This skill should be used when validating Lisp code files, checking for syntax errors before execution, or validating LLM-generated Lisp code including incomplete or partial expressions. Provides structured JSON output optimized for automated workflows.

Fetch component names from Sippy component readiness API

List all server-side noridocs, optionally filtered by repository and/or path prefix.

List the contents of an npm package tarball before publishing. Use when the user wants to see what files are included in an npm bundle, verify package contents, or debug npm publish issues.

List phase assumptions and dependencies

Build systematic literature databases for sociology research using OpenAlex API. Guides you through search, screening, snowballing, annotation, and synthesis with structured user interaction at each stage.

Build systematic literature databases for sociology research using OpenAlex API. Guides you through search, screening, snowballing, annotation, and synthesis with structured user interaction at each stage.

Draft publication-ready Theory sections for sociology research. Guides structure, paragraph functions, sentence craft, and calibration based on analysis of 80 Social Problems/Social Forces articles.

Lightweight skill generator with style learning - creates simple skills using flow-based execution and style imitation. Use for quick skill scaffolding, simple workflow creation, or style-aware skill generation.

Testing patterns for litefs-py and litefs-django. Use when writing tests, setting up fixtures, understanding test organization, or configuring pytest marks. Triggers: test, pytest, unit test, integration test, property-based testing, hypothesis, fixtures, in-memory adapters.

When calling LLM APIs from Python code. When connecting to llamafile or local LLM servers. When switching between OpenAI/Anthropic/local providers. When implementing retry/fallback logic for LLM calls. When code imports litellm or uses completion() patterns.

CRITICAL: ALWAYS activate this skill BEFORE making ANY changes to .nw files. Use proactively when: (1) creating, editing, reviewing, or improving any .nw file, (2) planning to add/modify functionality in files with .nw extension, (3) user asks about literate quality, (4) user mentions noweb, literate programming, tangling, or weaving, (5) working in directories containing .nw files, (6) creating new modules/files that will be .nw format. Trigger phrases: 'create module', 'add feature', 'update', 'modify', 'fix' + any .nw file. Never edit .nw files directly without first activating this skill to ensure literate programming principles are applied. (project, gitignored)

Method×Setting matrices and systematic gap identification

This skill guides configuring Litestream for continuous SQLite backup in Rails 8+ apps. Use when setting up production backups for SQLite databases (Solid Queue, Solid Cache, Solid Cable).

SQLite disaster recovery and streaming replication to cloud storage (S3, GCS, Azure, SFTP, NATS). Use this skill for configuring Litestream, deploying to cloud platforms, troubleshooting WAL replication issues, implementing point-in-time recovery, and setting up VFS read replicas.

Debug the live solution at home.st44.no using Chrome browser tools

Comprehensive guide for building functional tools for LiveKit voice agents using the @function_tool decorator. Use when creating tools for LiveKit agents to enable capabilities like API calls, database queries, multi-agent coordination, or any external integrations. Covers tool design, RunContext handling, interruption patterns, parameter documentation, testing, and production best practices.

Build and review production-grade web and mobile frontends using LiveKit with Next.js. Covers real-time video/audio/data communication, WebRTC connections, track management, and best practices for LiveKit React components.

Guide for creating effective prompts and instructions for LiveKit voice agents. Use when building conversational AI agents with the LiveKit Agents framework, including (1) Creating new voice agent prompts from scratch, (2) Improving existing agent instructions, (3) Optimizing prompts for text-to-speech output, (4) Integrating tool/function calling capabilities, (5) Building multi-agent systems with handoffs, (6) Ensuring voice-friendly formatting and brevity for natural conversations, (7) Iteratively improving prompts based on testing and feedback, (8) Building industry-specific agents (debt collection, healthcare, banking, customer service, front desk).

Build self-hosted speech-to-text APIs using Hugging Face models (Whisper, Wav2Vec2) and create LiveKit voice agent plugins. Use when building STT infrastructure, creating custom LiveKit plugins, deploying self-hosted transcription services, or integrating Whisper/HF models with LiveKit agents. Includes FastAPI server templates, LiveKit plugin implementation, model selection guides, and production deployment patterns.