Clawdex: A Directory for Tracking OpenClaw Derivatives and Forks
Clawdex is a directory created to track the proliferation of projects related to OpenClaw. It currently lists 18 projects organized into three tiers.
Project Tiers
The directory categorizes projects as follows:
- Tier 1: Direct clones and rewrites. Examples given include ZeroClaw, PicoClaw, IronClaw, and Moltis.
- Tier 2: Ecosystem projects. Examples given include Moltworker, ClawHub, and Moltbook (described as a social network for AI agents).
- Tier 3: Projects that are doing their own thing but were clearly inspired by the same idea.
Directory Features
Each listed project includes:
- Star count (fetched during build)
- Programming language
- Category tags
- Ability to filter and sort the entire directory
Contribution Process
Additions to the directory are PR-driven. The process is:
- Fork the repository.
- Drop a YAML file in
/src/data/projects/. - Open a pull request.
A CI system validates the schema of submitted YAML files. A human reviewer (the creator, as mentioned) then reviews and merges acceptable pull requests.
📖 Read the full source: r/clawdbot
👀 See Also
Claude Code Adds Multi-Agent Code Review System
Anthropic has launched Code Review for Claude Code, a multi-agent system that dispatches teams of AI agents to review pull requests. The system catches bugs human reviewers often miss, with 54% of PRs now getting substantive review comments compared to 16% before.
Connecting OpenClaw to Qwen2.5 Coder: Feasibility and Considerations
Explore the possibility of connecting OpenClaw to a local Qwen2.5 Coder model with 7 billion parameters to address rate limits with API Gemini 3.
Reasoning Guard: Proxy-Level Loop Detection for Local LLM Inference
A proxy-layer guard that detects and recovers from LLM reasoning loops using deterministic stream checks — token caps, n-gram repetition, and sentence fingerprinting — without model modifications.
OpenClaw Memos Plugin Addresses Memory Handoff Issues in AI Coding Agents
A Reddit user shares how the Claude code leak highlighted problems with memory handoff in AI coding agents, where bloated transcripts cause issues during model switching. They implemented the memos plugin in OpenClaw with selective recall strategy to compress recent work and drop stale tool calls.