Browse Skills

Provides scripts to backup, restore, and migrate Headscale installations, including SQLite database, configuration, policy, and certificates. Useful before upgrades or for disaster recovery.

Deploy and manage a self-hosted Tailscale ecosystem using Headscale as the open-source control server. Includes infrastructure setup, policy configuration, client onboarding, routing, and backup.

Chain web research, atomic extraction, and durable knowledge capture into a repeatable workflow when the same research-to-notes sequence is needed.

Documents brand strategy, visual identity, voice, and guidelines into markdown specs, compiled brand books, and brand-compliant images via reference-image-aware generation. Useful for agency handoff, press kits, or internal brand vaults.

Build conversational multi-agent AI systems with Microsoft AutoGen. Covers AssistantAgent, UserProxyAgent, GroupChat, code execution, nested chats, tool integration, and MCP support. Use for conversation-driven multi-agent orchestration.

Organize durable agent research outputs as summaries, analysis, and evidence dossiers. Use when producing multi-layer research artifacts or coordinating research handoffs.

CLI tool for managing Radarr (movies) and Sonarr (TV series) media libraries. Use for listing, adding, searching, checking queues, quality profiles, and more.

Guides the design, documentation, review, and evolution of consumer-facing APIs and event interfaces, including contract authoring, compatibility assessment, and deprecation planning.

Defines the Agent Skills open format, including directory structure, SKILL.md schema, naming conventions, and progressive disclosure model. Use this reference when creating, reviewing, or editing agent skills to follow the standard.

Design, run, review, or release framework- and vendor-neutral evaluations and observability for AI agents. Use when defining agent evals, datasets, graders, trajectory review, regression analysis, release gates, production traces, or privacy-aware telemetry.

Spawn a panel of expert AI agents to debate any question using a structured protocol with iterative cross-examination and convergence detection, producing a decision landscape with confidence diagnostics.

Write, review, and maintain architecture decision records with clear context, alternatives, consequences, and lifecycle governance. Use when a consequential technical decision must remain understandable.