OpenClaw Skill for Local Meeting Transcription with Whisper

A developer has released an OpenClaw skill called ghostmeet that enables local meeting transcription using OpenAI's Whisper model. This tool is designed to work with browser-based meetings like Google Meet, Zoom web, and Teams web.
How It Works
- A Chrome Extension captures audio from any browser tab using
chrome.tabCapture, limited to the active tab - Whisper transcribes the audio locally in real-time with approximately 10-second intervals
- Users can ask their assistant "summarize my last meeting" to get Claude-generated key decisions and action items
Privacy and Local Processing
- All audio and transcription processing happens locally on your machine using Whisper
- Summaries optionally use the Anthropic API, but this can be skipped for full privacy
- Desktop applications (Zoom app, Teams app) won't work - only browser tabs are supported
Setup and Installation
Install via ClawHub:
clawhub install ghostmeetOr set up manually:
git clone https://github.com/Higangssh/ghostmeet.git
docker compose up -dThe developer notes that speaker diarization is next on the roadmap and welcomes feedback on the project.
📖 Read the full source: r/openclaw
👀 See Also

Artificial-life: A 300-line Python reproduction of Computational Life research
A Python implementation reproducing the Computational Life paper, where 240x135 grid of Brainfuck-like programs interact and evolve self-replicating code through random pairing and instruction tape concatenation.

Fullerenes: Open-source persistent memory layer for coding agents cuts tokens by 64% on SWE-bench
Fullerenes uses a local SQLite knowledge graph built via Tree-sitter to give coding agents like Claude Code persistent memory, reducing token usage by 64% on SWE-bench and up to 96.6% on internal benchmarks.

Community patch adds RTL language support to Claude Desktop on Windows
A developer has created a patch that adds proper right-to-left language support to Claude Desktop on Windows, fixing broken rendering for Hebrew, Arabic, and other RTL languages. The patch injects RTL detection logic into the Electron app's renderer and includes backup/restore functionality.

MemAware benchmark shows RAG-based agent memory fails on implicit context retrieval
The MemAware benchmark tests whether AI agents can surface relevant past context when users don't explicitly ask for it, revealing that current memory systems score only 2.8% accuracy on hard implicit queries versus 0.8% with no memory.