Alternatives to grpo-rlvr-training
50 AI Skills apps to use instead, best rated first.
Top picks
- W
webapp-testing
LaunchNative Python Playwright scripts for testing local web applications with server lifecycle management. Includes with_server.py helper to automatically start and manage single or multiple servers before running automation scripts. Supports re
- C
content-research-writer
LaunchAssists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on
- O
openhue
Launchopenhue is an agent skill from the OpenClaw project, listed on skills.sh. It lets an agent control Philips Hue lights and scenes through a Hue Bridge with the OpenHue CLI: turn lights on and off, dim rooms, set scenes such as movie mode, an
- B
batch-grill-me
Launchbatch-grill-me is an agent skill from Matt Pocock's skills collection, listed on skills.sh. It interviews you relentlessly about a plan until you share an understanding. It maps decisions as a tree and asks every question it can answer now
- I
implement
Launchimplement is an agent skill from Matt Pocock's skills collection, listed on skills.sh. It implements work from a spec or tickets: it fetches the ticket, works test-first at agreed seams, runs type checks and tests as it goes, reviews the re
- F
frontend-design
LaunchDistinctive, production-grade frontend interfaces that reject generic AI aesthetics through intentional design choices. Guides aesthetic direction selection (brutalist, maximalist, retro-futuristic, luxury, organic, etc.) before implementat
More AI Skills apps
brainstorming
Transform rough ideas into fully-formed designs through structured questioning
finishing-a-development-branch
Guides completion of development work by presenting clear options
test-driven-development
Use when implementing any feature or bugfix, before writing implementation code
About grpo-rlvr-training
grpo-rlvr-training
Train reasoning and verifiable-task behavior
grpo-rlvr-training is an agent skill from the wshobson/agents collection for training reasoning and verifiable-task behavior in language models with GRPO (Group Relative Policy Optimization) and reinforcement learning from verifiable rewards (RLVR). It applies when task success can be checked algorithmically, such as a math answer that is right or wrong, or code that passes its tests, so the model can learn from a reward signal instead of from demonstrations or preference pairs. The skill is part of the wshobson fine-tuning sequence. It assumes the routing step has already decided that reinforcement learning is the right method, and it points to the separate skills for demonstration-based and preference-based training. The skill covers when RL is the right tool, a reference recipe for running GRPO, a mandatory gate that inspects the reward function before a run, and how to choose a GRPO variant when the base recipe behaves badly. The reward inspection step matters because a model will optimize whatever the reward measures, including shortcuts that do not reflect the real goal. It is installed with the skills CLI from the wshobson/agents repository. Its skills.sh page showed about 2.4K installs. The security audits showed Gen Agent Trust Hub with a warning, Socket passing and Snyk passing at the time of the scan.
- Price
- Free
- Made by
- wshobson
- Category
- AI Skills
- Website
- github.com/wshobson/agents/grpo-rlvr-training