Audits project dependencies for vulnerabilities. Multi-ecosystem support (npm, .NET, Python, Go). CVSS-based severity classification.

Configures CORS policy for development and production

Configures Swagger/OpenAPI documentation

Orchestrates final verification - build, test, and container health checks

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Specialized agent for multi-repository analysis, searching remote codebases, retrieving official documentation, and finding implementation examples using GitHub CLI, Context7, and Web Search. Use proactively when unfamiliar libraries or frameworks are involved, working with external dependencies, or needing examples from open-source projects to understand best practices and real-world implementations.

Configure build systems, optimize bundle size, manage exports for ESM/CJS/UMD, and publish packages to NPM with proper versioning

Standardized library design patterns for autonomous-dev including two-tier design, progressive enhancement, non-blocking enhancements, and security-first architecture. Use when creating or refactoring Python libraries.

Detect project stack from package manifests (package.json, pyproject.toml, go.mod, Cargo.toml, pubspec.yaml, CMakeLists.txt). Auto-identify frameworks, test tools, and build systems for onboarding.

License compliance checking and conflict detection

Navigate long-term life direction through reflective dialogue and decision frameworks. This skill helps you explore values, make significant decisions, and maintain intentional direction without endle

Sets up Lighthouse CI to automatically test performance, accessibility, SEO, and best practices in your CI/CD pipeline with budget enforcement and trend tracking.

Use this skill when the user mentions LimaCharlie or wants to work with endpoint detection, cloud security monitoring, detection rules, or security automation. This provides an overview of LimaCharlie components and their interconnections.

Use this skill when new users want to get started with LimaCharlie, set up their first organization, or begin collecting security data. Guides beginners through org creation and helps identify what to onboard, then hands off to specialized skills.

This skill provides a comprehensive workflow for implementing Linear issues with professional software engineering practices. It automates the entire development lifecycle from issue analysis through

Lightweight Linear skill for fetching issue details. Returns only essential data (title, description, state, assignee) to optimize context usage compared to full Linear MCP.

Linear issue tracking - MUST READ before using Linear commands

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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.

Build targeted prospect lists by analyzing LinkedIn profiles, extracting job titles, companies, locations, and recent activity. Identifies decision-makers, tracks job changes for warm outreach, and enriches contact data. Use when users need to find prospects, build lead lists, or track decision-maker movements.

This skill helps find meaningful connections between notes in the knowledge base.

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

Expert in AT-SPI2 (Assistive Technology Service Provider Interface) for Linux desktop automation. Specializes in accessible automation of GTK/Qt applications via D-Bus accessibility interface. HIGH-RISK skill requiring security controls for system-wide access.

Master essential Linux commands for system administration, security operations, and penetration testing. This skill covers user management, file permissions, disk management, LVM, networking, firewall

You are a Linux kernel development expert specializing in device drivers, kernel modules, and subsystem development. You follow strict kernel coding standards and use modern kernel APIs.

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

Specialized lipidomics analysis for lipid identification, quantification, and pathway interpretation. Covers LC-MS lipidomics with LipidSearch, MS-DIAL, and LipidMaps annotation. Use when analyzing lipid classes, chain composition, or lipid-specific pathways.

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.

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

Query and return raw JIRA bug data for a specific project

Creates event-driven email listeners that monitor for specific conditions (like urgent emails from boss, newsletters to archive, package tracking) and execute custom actions. Use when user wants to be notified about emails, automatically handle certain emails, or set up email automation workflows.

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.

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.

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).

Guide for building production-ready LiveKit voice AI agents with multi-agent workflows and intelligent handoffs. Use when creating real-time voice agents that need to transfer control between specialized agents, implement supervisor escalation, or build complex conversational systems.

Principles for writing simple, maintainable Laravel/Livewire code. Use when writing Livewire components, tests, or Blade views. Focuses on avoiding over-engineering.

Navigate and load project living documentation for context from .specweave/docs/internal/. Use when implementing features and needing project context, referencing ADRs for design decisions, or accessing specs and architecture docs. Provides table of contents for all documentation types.

Launch or resume Living Docs Builder independently. Generates comprehensive enterprise documentation from codebase analysis with AI-powered insights. LSP-enhanced by default for accurate API extraction.

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.

LlamaIndex Wolfram Alpha tool for computational knowledge queries, math solving, scientific calculations, and agent integration. Triggers: wolfram alpha, computational query, math solver, scientific calculation, WolframAlphaToolSpec.

This skill should be used when building production LLM applications in any language. It applies when implementing predictable AI features, creating structured interfaces for LLM operations, configuring language model providers, building agent systems with tools, optimizing prompts, or testing LLM-powered functionality. Covers language-agnostic patterns for type-safe contracts, modular composition, multi-provider support, and production deployment.

Use when user needs LLM system architecture, model deployment, optimization strategies, and production serving infrastructure. Designs scalable large language model applications with focus on performance, cost efficiency, and safety.

Expert LLM architect specializing in large language model architecture, deployment, and optimization. Masters LLM system design, fine-tuning strategies, and production serving with focus on building scalable, efficient, and safe LLM applications.

Consult multiple AI models (ChatGPT and Gemini) for their perspectives before presenting implementation plans to users.

LLM-powered documentation generation for narrative architecture docs, tutorials, and developer guides. Uses AI consultation to create contextual, human-readable documentation from code analysis and spec data.

Extract structured data from construction documents using LLMs. Process RFIs, submittals, contracts, specifications. Convert unstructured PDFs to structured JSON/Excel.

Implementing function calling (tool use) with LLMs for structured outputs and external integrations.

llm-gateway-routing