What does the Rl Policy Optimization AI skill do?
Best practices for reinforcement learning policy optimization. Use when working on RL agents, PPO, SAC, or reward design.
Why use Rl Policy Optimization on TypingMind?
Because you install it once and use it with any model. Rl Policy Optimization is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.
How do I install Rl Policy Optimization in TypingMind?
Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/domain/rl-policy-optimization. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.
Which AI models can use Rl Policy Optimization?
Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.
How many AI models can I use with Rl Policy Optimization?
As many as you like. As long as a model supports skills, you can use Rl Policy Optimization with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.
Is the Rl Policy Optimization AI skill free?
Yes. It is published on GitHub by aiming-lab under the MIT license. You only pay your own AI provider for the tokens you use.
What are AI skills?
An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.
How are AI skills different from plugins or MCP servers?
A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.
