---
title: "RL Policy Optimization - Air Market"
description: "You are training an agent by reinforcement learning, where small choices in the algorithm or the reward quietly decide whether it works. This gives Claude practices to follow for policy optimization…"
canonical: "https://airmarket.ai/app/rl-policy-optimization"
---

[Air Market](/) / [Data & Analytics](/category/data) / RL Policy Optimization

Skill by [AIMING Lab](/@aiming-lab)

# RL Policy Optimization

Practices to lean on while tuning an agent that learns

## What this does

You are training an agent by reinforcement learning, where small choices in the algorithm or the reward quietly decide whether it works. This gives Claude practices to follow for policy optimization work. Reach for it while building or debugging an agent, or while deciding how to shape a reward.

### Top 3 things it does for you

- Write or review a PPO or SAC implementation
- Think through a reward before training on it
- Check RL agent code against known practice

## Information

**RL Policy Optimization at a glance**

|  |  |
| --- | --- |
| Kind | Skill |
| Publisher | [AIMING Lab](/@aiming-lab) |
| Category | [Data & Analytics](/category/data) |
| Works with | Agent Skills - an open standard supported by 40+ agents |
| Version | 1.0 |
| Size | 1 KB |
| Licence | MIT |
| Repository | [aiming-lab/AutoResearchClaw](https://github.com/aiming-lab/AutoResearchClaw/tree/84dad0a401404739cfcc47851cd1d282b671bb2f/researchclaw/skills/builtin/domain/rl-policy-optimization) |
| GitHub stars | 14,165 (as of Nov 2026) |

## Security report

**Verified.** AIR scanned this exact version of RL Policy Optimization and flagged nothing. AIR's verdict: **safe**.

**What RL Policy Optimization's check was run against**

|  |  |
| --- | --- |
| Commit | 84dad0a401404739cfcc47851cd1d282b671bb2f |
| Content hash | 844c98d5dac89e607f6fb9739cee6439d51ebfacdfb78ba0967f2853d39510d3 |
| Files read | [Browse the files at this exact commit](https://github.com/aiming-lab/AutoResearchClaw/blob/84dad0a401404739cfcc47851cd1d282b671bb2f/researchclaw/skills/builtin/domain/rl-policy-optimization/SKILL.md) |

A scan is named by the exact content it read, not by a version number. A different version is a different artifact, and nothing here applies to a version AIR has not scanned.

[Read the full security report for RL Policy Optimization](/security/rl-policy-optimization)

## About RL Policy Optimization

This covers best practices for reinforcement learning policy optimization.

It applies when you are working on RL agents, on PPO or SAC, or on reward design.

## What's inside

- SKILL.md - instructions

## Questions

### Is RL Policy Optimization safe to install?

AIR scanned this exact version of RL Policy Optimization and flagged nothing. AIR's verdict: safe. The verdict is named by the content that was read, at commit 84dad0a40140, so it cannot drift onto a version nobody scanned. The full report is at https://airmarket.ai/security/rl-policy-optimization.

### How do I install RL Policy Optimization?

Open https://airmarket.ai/app/rl-policy-optimization on Air Market and use the install action: Air Market hands Claude a prompt naming this exact skill, and Claude sets it up. Source, pinned to the exact commit this listing describes: https://github.com/aiming-lab/AutoResearchClaw/tree/84dad0a401404739cfcc47851cd1d282b671bb2f/researchclaw/skills/builtin/domain/rl-policy-optimization. Install from that link, not the branch.

## Related on Air Market

- [More Data & Analytics listings](/category/data)
- [Everything by AIMING Lab](/@aiming-lab)

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Canonical URL: <https://airmarket.ai/app/rl-policy-optimization>