Overview#

This page answers one question: what OpenProgram can do, and which page covers each capability. Capabilities come in three layers: the programming paradigm, ready-made workflows, and extension mechanisms.

The Agentic Programming paradigm#

OpenProgram is built on Agentic Programming: Python controls the flow, the LLM provides the reasoning. You decompose a task into a function call graph — nodes that need no reasoning are plain Python, nodes that need understanding / generation / judgment are decorated with @agentic_function and call the model via runtime.exec(...) inside the function body. Execution order, state, and retries are ordinary code you can unit-test.

• Agentic Programming guide — the learning path for writing functions and the three "choose the next step" mechanisms
• Design philosophy — what problem the paradigm solves and why it inverts control

Agentic workflows: ready-made agents#

Complete workflows written on top of the paradigm (called harnesses / agentic programs in the code), usable right after install: GUI automation, autonomous research, a personal knowledge base. See what is installable with openprogram programs available, install with openprogram programs install <name>, list the registered functions with openprogram programs list; once registered, the functions can be triggered as tools in chat or run directly with openprogram programs run.

• Agentic workflows overview
• GUI Agent — give it one task sentence, it operates the desktop autonomously
• Research Agent — from topic selection to a submittable paper
• Wiki Agent — distills sessions into an HTML knowledge base
• Installing and writing harnesses — the install mechanism and directory contract for third-party harnesses

Extension mechanisms#

Ways to extend the agent's capabilities without writing a harness:

• Skills — the SKILL.md registry: domain knowledge and playbooks the model loads on demand
• Distill — turn a session that worked into a reusable skill or function, so the procedure survives the conversation
• Commit, push, PR — take finished work from the working tree to a reviewable pull request, with AI co-author attribution in git log
• Plugins — install plugins from pip / npm / git / local paths that contribute commands, skills, MCP servers, and more to the host
• MCP — connect any MCP server; its tools appear directly in chat
• Built-in tools — the tools that ship with the framework (shell, files, web search, images, PDF, etc.) and the keys each one needs