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
AgentWorkingMemory: A Local Memory System for AI Coding Agents
AgentWorkingMemory (AWM) is a local memory system that solves the session-to-session amnesia problem in AI coding agents. It uses a SQLite database, three local ML models (~124MB total), and integrates automatically via MCP to provide persistent, context-aware memory across Claude Code sessions.
Anthropic Open-Sources Claude for Legal: Plugin Suite for Contract Review, NDA Triage, and More
Anthropic released Claude for Legal, a repo of plugins, agents, and MCP connectors for legal workflows including vendor agreement review, NDA triage, and regulatory monitoring.
Replacing complex retrieval pipelines with simple git shell commands for LLM agents
A developer replaced their entire AI agent retrieval pipeline (sentence-transformers, rank-bm25, two-pass LLM pipeline) with a single tool that lets the agent execute read-only shell commands against a git repository, reducing Docker image size by ~3GB and eliminating timeout issues.
NLA Transforms Gemma 3’s Internal Activations into Readable Text for Any Token
Anthropic released Natural Language Autoencoders (NLA) that decode a model’s internal state into text. Paired with Gemma 3, the Auto Verbalizer explains what the model was “thinking” for any generated token. Weights are on Hugging Face; demo on Neuronpedia.