Prime Agent is an open-source coding and research agent
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.
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.
Everything is programmatic: persistent IPython is
the built-in model tool; file operations, shell commands, tool use,
subagents, and context management happen through code.
Subagents are built in:rlm(...) 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.
Getting Started
Install the latest stable release on macOS or Linux:
curl -fsSL https://app.primeintellect.ai/prime-agent/install.sh | sh
The installer downloads a versioned release, verifies its SHA-256 checksum, installs the prime-agent command, and can prepare the IPython runtime used by the agent.
Start Prime Agent from the repository or directory you want it to work in:
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,
skills, and extensions only. Run untrusted code or instructions in an
external sandbox or restricted environment.
Useful commands:
prime-agent agents # Browse running, idle, and saved sessions
prime-agent attach <agent># Reattach to a running session
prime-agent --resume <path|id># Resume a saved session
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
Built for Long-Running Work
Prime Agent is built for long-running work, especially for
evaluations in research. These features are available in the TUI, and
when run autonomously.
Continual Harness:/refine can persist
focused, reviewable lessons as supplemental prompts, memories, reusable
skill descriptions, or subagent specifications, with recorded
refinement history. It does not replace packaging and reviewing new
executable skills.
Direct agent-to-agent communication: running agents and retained subagents can discover one another, exchange messages, and steer active work.
Daemon-backed continuity: active sessions, IPython state, schedules, and subagents keep running when the terminal detaches and can be reattached later.
Heartbeats and schedules:/heartbeat, rlm_heartbeat, and prime-agent schedule can re-enter a session periodically or at a specific time.
Persistent goals:/goal keeps an objective and its progress active across turns until it is completed, paused, or cleared.
Bounded autonomous mode:/autonomous
continues within configured turn, token, and time budgets and can run
user-defined quality gates. A passed gate checks only what that gate
verifies; reaching a limit does not imply task success.
Documentation
Quickstart — install, authenticate, and run a first session
