SwarmClaw Dashboard Adds Orchestration Layer to OpenClaw
SwarmClaw is a self-hosted dashboard that adds a full orchestration layer on top of OpenClaw, allowing developers to deploy and manage multiple OpenClaw instances from a single interface.
Key Features
- Per-agent gateway toggling for individual instance control
- Built-in gateway controls with reload mode switching
- Config issue detection and repair capabilities
- Remote history sync between instances
- Live execution approval handling
- Direct support for OpenClaw plugins
- SKILL.md file support with frontmatter
- Connects to 14 other AI providers including Anthropic, OpenAI, Gemini, and Ollama for mixed setups
Getting Started
Install and run with these commands:
npm i -g @swarmclawai/swarmclaw
swarmclawThe tool is available on GitHub at github.com/swarmclawai/swarmclaw.
This type of orchestration tool is useful for teams running multiple AI coding agent instances who need centralized management and monitoring capabilities.
📖 Read the full source: r/clawdbot
👀 See Also
Recall: Local Project Memory for Claude Code — No Tokens Spent on Summaries
Recall gives Claude Code durable, local session memory via classical summarization. No API key, no external model — context.md is ~1-2K tokens, built offline from session hooks.
SkyClaw: Rust-Based Autonomous AI Agent Runtime
SkyClaw is an autonomous AI agent runtime built in Rust with a 7.1 MB binary that idles at 14 MB RAM and starts in under one second. It operates on five engineering principles including autonomy, robustness, and brutal efficiency.
SigMap v8.9: Deterministic Context Layer Cuts Token Use 97% for AI Coding Agents
SigMap v8.9 achieves 97% token reduction, 88% hit@5 retrieval, and 49% fewer prompts per task. Works with Copilot, Claude Code, Cursor, Windsurf, Codex, OpenCode, Gemini CLI. Zero deps, fully offline.
Qwen 3.6 27B hits 2.5x speed with MTP speculative decoding on llama.cpp
A Reddit user reports 2.5x faster inference on Qwen 3.6 27B using MTP speculative decoding with a custom llama.cpp PR, achieving 28 tok/s on Mac M2 Max 96GB. Includes pre-converted GGUF quants and fixed chat templates.