Yaowei ZhengandClaude Opus 4.8
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
72 lines
4.0 KiB
Markdown
72 lines
4.0 KiB
Markdown
---
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title: "Introducing PenguinHarness: agents that build agents"
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date: 2026-07-17
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category: news
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excerpt: The first open-source harness with recursive self-improvement is here — lightweight, efficient and secure infrastructure covering everything from automatic agent construction to continuous self-evolution.
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---
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Today we are releasing **PenguinHarness** — an open-source harness built for constructing and evolving agents. Its purpose fits in one line:
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> Efficient Self-Improving Harness for Everyone.
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## Why PenguinHarness
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Over the past year the way agent applications are built has been converging fast: what really decides quality is not a heavyweight framework but a simple, reliable, observable harness. PenguinHarness is rebuilt from the ground up — no dependency on any agent framework, a fully open-source self-developed kernel — and it brings three things to the open-source world first:
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- **Simplest Is the Best**: a deliberately minimal toolset over clean low-level interfaces — fewer tool calls, fewer Tokens, complex tasks done efficiently.
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- **Harness for Building Agents**: with the PenguinHarness SDK, an Agent builds complete Agent applications for you, autonomously, from scratch.
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- **Harness for Recursive Self-Improvement**: with PenguinHarness Skills, an Agent evaluates and optimizes itself, improving recursively over time.
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For the latter two, PenguinHarness is the first open-source implementation in the industry.
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## Same model, equal or better quality, lower cost
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All runs use the same DeepSeek V4 Pro model, head-to-head against Claude Code and OpenAI Codex on two suites (per-run means below).
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Complex data analysis (15 tasks, single run):
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| Framework | Model | Accuracy (%) | Tokens (M) | Cost ($) |
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| --- | --- | ---: | ---: | ---: |
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| PenguinHarness | DeepSeek V4 Pro | 66.7 | 18.04 | 0.552 |
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| Claude Code | DeepSeek V4 Pro | 66.7 | 21.17 | 0.641 |
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| OpenAI Codex | DeepSeek V4 Pro | 46.7 | 13.36 | 0.427 |
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Coding tasks (40 tasks × 2 runs averaged, thinking high, 30 min per-case timeout, CNY pricing converted at $1 = ¥7):
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| Framework | Model | Accuracy (%) | Tokens (M) | Cost ($) |
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| --- | --- | ---: | ---: | ---: |
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| PenguinHarness | DeepSeek V4 Pro | 50.00 | 2.10 | 0.041 |
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| Claude Code | DeepSeek V4 Pro | 48.75 | 2.00 | 0.048 |
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| OpenAI Codex | DeepSeek V4 Pro | 42.50 | 2.65 | 0.043 |
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On the data-analysis suite PenguinHarness ties Claude Code on accuracy and clearly beats OpenAI Codex while using 14.8% fewer Tokens at 13.8% lower cost; on the coding suite it scores highest of the three at the lowest per-run cost.
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## Evolution within bounds, security first
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The biggest worry about self-improvement is losing control. PenguinHarness answers with a contract — CONTRACT.md:
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- Evolution is strictly confined to Workspace and Skills; the harness core security boundary is never modified.
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- Tool calls run only after approval, and every approval is audited.
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- Risky changes snapshot first — every step of evolution can be rolled back.
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- Fully open source and locally deployable: data never leaves your machine, meeting enterprise security requirements.
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## Get started now
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Install with one command (Linux / macOS, x64 / arm64, bundled Node runtime):
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```bash
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curl -fsSL https://github.com/Prism-Shadow/penguin-harness/releases/latest/download/install.sh | sh
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```
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Configure a model (DeepSeek as an example), run your first task, or open the desktop-grade web interface with `penguin web`:
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```bash
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penguin config model add --model-id deepseek-v4-pro --api-key sk-your-key --set-default
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penguin run --approve allow-all --message "Analyze data.csv and summarize quarterly sales"
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penguin web
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```
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PenguinHarness supports 1000+ online and local models and multi-agent collaborative evolution, and runs on as little as a single CPU. Through continuous evolution it makes complex AI development ever simpler — a more efficient, more reliable, lower-hallucination and lower-cost Agent productivity engine.
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Follow us on [GitHub](https://github.com/Prism-Shadow/penguin-harness) and open your first issue.
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