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Introduction What PenguinHarness is, what ships in the box, and the design tenets behind it.

PenguinHarness is an open-source AI Agent harness — a complete TypeScript stack built for constructing and evolving agents. It deploys fully locally (your data never leaves the machine), runs on as little as a single CPU, and reaches 1000+ online and local models through one unified model gateway.

In one line: Efficient Self-Improving Harness for Everyone.

The three pillars

PenguinHarness is organized around three radiating concepts — the message protocol, the SDK, and the skill library — each carrying one pillar:

Pillar Meaning
Simplest Is the Best A deliberately minimal toolset over clean low-level interfaces: fewer tool calls, fewer Tokens, complex tasks done efficiently.
Harness for Building Agents With the PenguinHarness SDK, an Agent builds complete Agent applications for you — autonomously, from scratch.
Harness for Recursive Self-Improvement With PenguinHarness Skills, an Agent evaluates and optimizes itself, improving recursively over time.

What ships in the box

One install gives you four layers that share a single data directory and a single message protocol:

Component Package Description
SDK @prismshadow/penguin-core The core engine: ReAct loop, the OmniMessage protocol, the LLM and Environment interface contracts, Agent State and Trace.
CLI @prismshadow/penguin-cli The penguin command: interactive REPL, one-shot task runs, model and Vault configuration.
Server @prismshadow/penguin-server The Web backend: HTTP API and SSE streaming, multi-user auth, Project authorization, usage statistics.
Web App @prismshadow/penguin-web The browser UI: multi-session chat, Agent management, skill library, model configuration, Trace observability and the evaluation center.

Design tenets

These principles run through every component; the design pages keep coming back to them:

  • A minimal toolset: dedicated file tools (read_file / edit_file / write_file) for precise reading and editing, with the shell (exec_command) as the general-purpose fallback for everything else. See Tools & Approval.
  • Agents are editable data: prompts, Skills and config are editable files on disk, not hardcoded constants — what you can see, an Agent can improve. See the Configuration Reference.
  • Everything observable: every request, tool call and approval decision is appended to the Trace; a Session restores fully from it.
  • Errors converge into messages: model and tool failures never throw — they become messages the model can react to. See The Agent Loop.
  • Streaming first: text streams token by token; tool calls and results appear live.
  • Model ↔ Agent decoupling: an Agent never binds to a model; you pick one per Session. See Models & Providers.

A note on naming

The unified message protocol is called OmniMessage in technical writing (marketing materials also call it Penguin Message). This documentation uses OmniMessage throughout.

Next steps

  • Install PenguinHarness, then run your first Task with the Quickstart.
  • Start the design docs at the Architecture overview to see how the pieces fit together.