Woodander Discover
NEW IN MEDIA · GUIDE What Is Woodander? A Growth Platform for Projects That Want to Be Found
Woodander Discover Explore projects and businesses Add your project → Woodander TOP Competitive project rankings Claim a spot → Woodander Media News, stories and analysis Write a story → Woodander Market Advertising and partnerships List your channel → Woodander SEO Tools and content growth Check my website → Woodander Outreach Find relevant opportunities Build my route →

Layer vs LLM Fuzz CI

Both are on Woodander. Here is what each one does, who it is for and how they differ — from what the makers and our editors wrote.

Layer LLM Fuzz CI
What it is One API for prediction markets. Find markets, stream normalized data, place orders, and track positions across Kalshi and Polymarket. A GitHub Action that lets a coding agent write adversarial inputs for your tests, and reports only the ones that fail.
Category AI Apps & Assistants AI Apps & Assistants
Pricing — —
Page maintained by Woodander editors Woodander editors
On Woodander since October 2026 October 2026
Website uselayer.sh tiime-software.github.io

About Layer

One API for prediction markets. Find markets, stream normalized data, place orders, and track positions across Kalshi and Polymarket. Hi HN, I'm David. I built Layer, an API + SDK or building trading bots/ai agents across prediction markets.The idea came from something i kept running into while playing with trading bots. Once your bot needs access to more than 1 venue, you suddenly have to deal with different market schemas, contract definitions, prices, fees and APIs before you can reason about where to trade. That gets messy real fast, especially with prediction markets. The same real-world event can exist on Kalshi & Polymarket, but the contracts can be represented differently.Here's my broader thesis:...

Choose Layer if you need one API for prediction markets. Find markets, stream normalized data, place orders, and track positions across Kalshi and Polymarket.

Full page →

About LLM Fuzz CI

A GitHub Action that lets a coding agent write adversarial inputs for your tests, and reports only the ones that fail. Hi HN!Most of the explanation is in the blog post, and the code lives there: https://github.com/tiime-software/llm-fuzz-ci/Happy to receive feedback, and to know how other people use agents to improve code security!

Choose LLM Fuzz CI if you need a GitHub Action that lets a coding agent write adversarial inputs for your tests, and reports only the ones that fail.

Full page →

Other options

All Layer alternatives →
Woodander Discover keep growing.