# Prime Agent: A Self-Improving RLM Agent for Coding and Autonomous Tasks

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Prime Agent is an open-source, self-improving Recursive Language Model (RLM) agent designed for coding workflows and long-running autonomous tasks. It integrates a persistent Python control environment with a durable harness state, allowing useful context and reusable patterns to persist across sessions. Built in Rust, this project aims to enhance developer productivity through programmatic control and autonomous capabilities.

GitHub: https://github.com/PrimeIntellect-ai/prime-agent
OSRepos URL: https://osrepos.com/repo/primeintellect-ai-prime-agent

## Summary

Prime Agent is an open-source, self-improving Recursive Language Model (RLM) agent designed for coding workflows and long-running autonomous tasks. It integrates a persistent Python control environment with a durable harness state, allowing useful context and reusable patterns to persist across sessions. Built in Rust, this project aims to enhance developer productivity through programmatic control and autonomous capabilities.

## Topics

- Rust
- AI Agent
- LLM
- Autonomous Agent
- Coding Assistant
- RLM
- Developer Tools

## Repository Information

Last analyzed by OSRepos: Fri Oct 02 2026 12:38:21 GMT+0100 (Western European Summer Time)
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## Safety Notice

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## Content

## Introduction

Prime Agent is an open-source coding and research agent built for general and long-running work. It is designed around two core abstractions:

*   The **Recursive Language Model (RLM)** treats context as variables (prompt-as-a-variable) and tools like recursive subagents as function calls (programmatic tool/sub-agent calling) inside a persistent REPL.
*   The **Continual Harness** stores supplemental prompts, memories, skill descriptions, and reusable subagent specifications as durable state that Prime Agent can refine through small, evidence-backed updates, local to the session by default.

## Why Use and Key Benefits

Prime Agent combines a persistent Python control environment with durable harness state, so useful working context and reusable operating patterns can outlive a single chat window. Key benefits include:

*   **Everything is programmatic:** A persistent Python REPL is the built-in model tool; file operations, shell commands, tool use, subagents, and context management happen through code.
*   **Subagents are built in:** `rlm.spawn(...)` spawns real child agents for parallel or background work and returns their results programmatically.
*   **The harness can improve:** `/refine` reviews the current trajectory and can apply small, evidence-backed updates to supplemental harness state. It never rewrites the immutable base system prompt, and recorded snapshots support rollback.
*   **Skills are executable:** Skills are importable Python packages, and the built-in skill creator can turn recurring workflows into project or personal skills.
*   **Sessions run in the background:** Daemon-backed agents keep running when the terminal disconnects and can be reattached later.
*   **Agents communicate directly:** Running agents can exchange messages and orchestrate one another without routing everything through the user.
*   **Long tasks keep moving:** Automatic compaction, persistent goals, heartbeats, schedules, autonomous mode, and retained subagents preserve progress across turns and terminal sessions.

## Installation

Install the latest build with the one-command installer (every push to the `rust` branch publishes a fresh rolling beta; the stable channel ships on release):

For Linux/macOS:

bash
curl -fsSL https://app.primeintellect.ai/prime-agent/install.sh | sh


On Windows, install from PowerShell:

powershell
irm https://app.primeintellect.ai/prime-agent/install.ps1 | iex


The `sh` one-liner also works under Git Bash on Windows. Both installers publish the same layout (the launcher under `$HOME\.local\bin`, the payload under `$HOME\.local\share\prime-agent`) and read the same release channel: darwin (arm64/x64), linux (arm64/x64), and windows (x86_64, `win32-x64`).

## Examples

Start Prime Agent from the repository or directory you want it to work in:

bash
cd /path/to/project
prime-agent


On first launch, run `/login` to choose a subscription or API-key provider. Prime Agent works in the current directory and can run commands and modify files there. Use a disposable clone, clean worktree, or another checkpoint you can inspect and restore.

> **WARNING**
> Prime Agent executes model-generated Python and project commands with your user permissions. Its worker and kernel processes improve lifecycle isolation and recovery; they are **not** a security sandbox. Review changes and use trusted repositories, instructions, and skills only. Run untrusted code or instructions in an external sandbox or restricted environment.

Useful commands:

bash
prime-agent agents                   # Browse running, idle, and saved sessions
prime-agent attach <agent>           # Reattach to a running session
prime-agent --resume [path|id]       # Browse sessions or resume one directly
prime-agent status                   # Inspect background service state
prime-agent doctor [--fix]           # Inspect or repair background services
prime-agent update [--force]         # Update Prime Agent
prime-agent shutdown [--force]       # Stop every agent, worker, and background service


## Links

*   GitHub Repository: [PrimeIntellect-ai/prime-agent](https://github.com/PrimeIntellect-ai/prime-agent){target="_blank"}
*   Prime Intellect Website: [primeintellect.ai](https://primeintellect.ai){target="_blank"}
*   Verifiers Repository: [PrimeIntellect-ai/verifiers](https://github.com/PrimeIntellect-ai/verifiers){target="_blank"}
*   PRIME-RL Repository: [PrimeIntellect-ai/prime-rl](https://github.com/PrimeIntellect-ai/prime-rl){target="_blank"}
*   RLM Blog Post: [The Recursive Language Model](https://www.primeintellect.ai/blog/rlm){target="_blank"}
*   Prime Agent arXiv Paper: [2608.23552](https://arxiv.org/abs/2608.23552){target="_blank"}
*   Continual Harness arXiv Paper: [2605.09998](https://arxiv.org/abs/2605.09998){target="_blank"}