Unified linter runner. One command, JSON output, all issues sorted by file:line.
Skills（SKILL.md）は、AIエージェント（Claude Code、Cursor、Codexなど）に特定の能力を追加するための設定ファイルです。
詳しく見る →Unified linter runner. One command, JSON output, all issues sorted by file:line.
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.
Generate SwiftUI LiquidGlass components + tokens + accessibility + perf checks for iOS 26+/watchOS 26+.
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
Retrieve and display message history from Sinch Conversation API. Use when the user asks to show messages, view conversation history, list recent messages, see messages with a contact, check message history, or view last N messages. Supports filtering by contact, conversation, channel, and time range.
List all server-side noridocs, optionally filtered by repository and/or path prefix.
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.
Use when user wants to inventory autonomy branches with custom sorting, grouping, or filtering
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.
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.
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.
Fish farming domain knowledge for catfish and tilapia in LivestockAI
Poultry farming domain knowledge for broilers and layers in LivestockAI
Cattle, goats, and sheep farming domain knowledge in LivestockAI
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.
Expert LLC operations management for ID8Labs LLC (Florida single-member LLC). 9 specialized agents providing PhD-level expertise in compliance, tax strategy, asset protection, and business operations. Triggers on keywords like LLC, taxes, expenses, annual report, EIN, compliance, bookkeeping, deductions, filing, sunbiz, quarterly, S-Corp, retirement, audit, insurance, cash flow, mentor, teach, learn.
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
Advanced LLM jailbreaking techniques, safety mechanism bypass strategies, and constraint circumvention methods
Test llm-mux IR translator - cross-format API translation
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Comprehensive LLM model evaluation and ranking system. Use when users ask to compare language models, find the best model for a specific task, understand model capabilities, get pricing information, or need help selecting between GPT-4, Claude, Gemini, Llama, or other LLMs. Provides benchmark-based rankings, cost analysis, and use-case-specific recommendations across reasoning, code generation, long context, multimodal, and other capabilities.
U-llm-sdk and claude-only-sdk patterns. Use when working on projects with LLM service, designing LLM integrations, or implementing AI-powered features.
Comprehensive system for managing llms.txt and my-blog.json files across the project. Handles creation, updating, and synchronization of AI-readable content catalogs. Automatically detects when working with llms.txt files, my-blog.json files, or updating blog content. Includes utilities for fetching latest content from query-index.json and organizing by last modified dates. Keywords include llms.txt, my-blog.json, blog catalog, content index, query-index.json, AI content discovery, update llms, update blog, content synchronization.
Generate an llms.txt file for any project or website following the llmstxt.org specification. Use when asked to create llms.txt, generate LLM-friendly documentation, make a project AI-readable, or prepare documentation for language models.
LMS feature implementations including Browse Gradebook, Course Kanban, Communications, Statistics Module, MAP Analytics, Teacher Schedule, and Attendance System. Use this skill when implementing or modifying these features, understanding their data structures, or debugging feature-specific issues.
Top orchestrator for complete doc system. Delegates to ln-110 coordinator (project docs via 5 L3 workers) + ln-120-150 workers. Phase 4: global cleanup. Idempotent.
Coordinates project documentation creation. Gathers context once, detects project type, delegates to 5 L3 workers (ln-111-115). L2 Coordinator invoked by ln-100.
Creates 2 backend docs (api_spec.md, database_schema.md). L3 Worker invoked CONDITIONALLY when hasBackend or hasDatabase detected.
Creates test documentation (testing-strategy.md + tests/README.md). Establishes testing philosophy and Story-Level Test Task Pattern. L2 Worker in ln-100-documents-pipeline workflow.