prime-agent

GitHub describes it as A self-improving RLM agent for coding workflows and long-running autonomous tasks.. The repository metadata lists TypeScript as its primary language. The metadata lists the MIT license. This article stays within the project description and details documented in the GitHub repository README.

GitHub describes it as A self-improving RLM agent for coding workflows and long-running autonomous tasks.. The repository metadata lists TypeScript as its primary language. The metadata lists the MIT license. The README describes the project this way: Prime Agent is an open-source coding and research agent for general and long-running work. It is designed around two core abstractions:

The README section "README details" states: - 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.

The README section "README details" states: 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.

The README section "README details" states: - 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.

The repository README is the source for this review. It does not replace a local installation or an independent test.

• Source 1 · Project repository
• Source 2 · README