claudectl vs Skrun

Claudectl is a free, open-source terminal supervisor for running multiple Claude Code sessions from a single unified dashboard. Instead of hunting between tabs to check on parallel agent runs, you get real-time visibility into status, spend rate, context window usage, CPU, and memory for every active session simultaneously. The operational features are where it earns its keep: set per-session budget caps that automatically kill runaway agents before they drain your API credits, approve pending prompts from the dashboard without switching contexts, and run dependency-ordered workflows where task completion triggers the next step. Desktop notifications, shell hooks, and webhooks fire when a session needs attention. For teams scaling autonomous coding work, claudectl also records sessions as GIFs or terminal casts — useful for documentation, debugging, or showing clients what the agent actually did. It installs via Homebrew or Cargo, supports macOS and Linux across eight terminal emulators, and ships with a demo mode for risk-free evaluation. A genuinely useful piece of infrastructure that fills a gap Anthropic hasn't addressed natively yet.

Skrun is an open-source tool that wraps agentic skills — the discrete, reusable capabilities you build for AI agents (web search, data extraction, file transformation, API calls) — into deployable REST APIs with a single command. The idea is that skills you build for one agent context shouldn't be locked to that agent's runtime. With Skrun, you define a skill once with a standard function signature, and get a hosted endpoint with automatic request validation, retry logic, rate limiting, and an OpenAPI spec generated automatically. The project addresses a real architectural tension in the current AI tools ecosystem: agent skills are written in a dozen different formats (LangChain tools, MCP tools, function call JSON, OpenAI tool specs) and are essentially stranded assets — they only work within their specific orchestration framework. Skrun normalizes this by wrapping any skill definition format and exposing it as a framework-agnostic HTTP endpoint that any agent or pipeline can call. This appeared on Hacker News with a small but thoughtful discussion focused on the "skills as microservices" architectural pattern. Critics noted that adding HTTP round-trips to every tool call introduces latency; proponents argued that the composability and reusability benefits outweigh the cost. The early version focuses on stateless skills; stateful/conversational skill deployment is on the roadmap.