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Found 1,685 Skills
Deep Reading Collaborative System: A system leveraging multi-layered AI Agents to help transform articles from "read" to "understood" to "mastered", and convert knowledge into actionable plans. Use this system when you need to deeply understand complex articles/papers, systematically organize reading notes, think critically about content, discover hidden logical issues and assumptions, or turn knowledge into action plans. Trigger keywords: deep reading, critical thinking, reading notes, article analysis, Socratic questioning, action plan
General Architecture Governance Specification, providing layering constraints, impact analysis, interface contracts, and dependency injection baselines. Suitable for architecture review, refactoring, and new module design of any multi-layer system.
Access Finland's Wilma school system from AI agents. Fetch schedules, homework, exams, grades, messages, and news via the wilma CLI. Start with `wilma summary --json` for a full daily briefing, or drill into specific data with individual commands.
Security audit enforcement for AI agents. Automated security scans and health verification.
Project setup. Explore the codebase, ask about strategy and aims, write persistent context to AGENTS.md. Run when starting or when aims shift.
Guide for creating effective AI agent skills. Use when users want to create a new skill (or update an existing skill) that extends an AI agent's capabilities with specialized knowledge, workflows, or tool integrations. Works with any agent that supports the SKILL.md format (Claude Code, Cursor, Roo, Cline, Windsurf, etc.). Triggers on "create skill", "new skill", "package knowledge", "skill for".
Complete Hindsight documentation for AI agents. Use this to learn about Hindsight architecture, APIs, configuration, and best practices.
Make generated speech feel companion-like with fillers, emotional tuning, and preset speaking styles.
Operate long-lived agent workloads with observability, security boundaries, and lifecycle management.
Engineering operating model for teams where AI agents generate a large share of implementation output.
Access 1200+ AI Agent tools via Model Context Protocol (MCP)
Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.