Yaowei Zheng
45bfae6e94
Initial import of all source code, config, and README assets: the packages workspace (cli, core, server, web, docs, landing, skills), build scripts, tooling config, and CI workflows. Includes the data-layout revision made on this branch: the local data root defaults to ~/.penguin/data (PENGUIN_HOME still overrides; the installer keeps its binaries in ~/.penguin), and every Agent lives under <project>/agents/<agent>/ — path helpers, the three agent-enumeration scans, the system prompt, built-in Skills, tests and docs all follow the new layout. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_018ihk8iQuo3kv2aPjAYEPuR
3.4 KiB
title, description
| title | description |
|---|---|
| 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: the shell is the universal interface — file reads, writes and edits all go through
exec_command. 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.