Developer Tool / AI Safety / Security
Python framework for conversational social engineering detection using a finite state machine. The README says it tracks turn-by-turn signals like flattery density, give/ask ratio, escalation velocity, and scope mismatch, and exposes a simple `Xtra().analyze(turns)` usage example.
The page clearly describes an AI-adjacent developer tool with a concrete purpose: detecting conversational social engineering attempts in Python. The README gives a working mental model of how it operates, names the main signals it tracks, and shows a usage snippet, which is enough for a useful public listing.
The crawl only shows a short README and one usage example. It does not show installation instructions, API details beyond the basic call, test coverage, releases, or any evaluation data demonstrating how accurate the detector is.
Last evaluated 66 days ago. Current rank #1728. Holding steady in the rankings.
A Rust Blu-ray disc analyzer that reimplements BDInfo for BDMV folders and ISO images, with CLI, desktop, and browser/WASM front ends.
WebLLM is a high-performance in-browser LLM inference engine that runs locally in the browser with WebGPU acceleration. It exposes an OpenAI-compatible API, supports streaming and JSON mode, and includes examples for building chat apps and browser extensions.
Molt is an open protocol for letting an AI agent make bounded purchases through disposable, single-use payment credentials. The repo includes a clear quickstart, MCP integration, a threat model, and a working test-mode demo.
Self-hosted observability and control plane for production and coding AI agents, with live timelines, fleet-wide feeds, token budgets, MCP allow/block rules, and support for Claude Code plus a Python sensor.
