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Ralph Evolver

作者 Sky Hai · GitHub ↗ · v1.0.6
cross-platform ⚠ suspicious
3714
总下载
8
收藏
14
当前安装
7
版本数
在 OpenClaw 中安装
/install ralph-evolver
功能描述
Recursive self-improvement engine. Think from first principles, let insights emerge.
安全使用建议
This skill appears to implement what it promises (analyzing a repo and tracking improvements), but there are a few practical risks to consider before installing/using it: - Manifest discrepancy: The code invokes git and grep and requires Node.js (package.json) but the registry metadata declares 'required binaries: none'. Expect to need git, grep, and Node >=18. Ask the publisher to update the manifest if you need that guarantee. - It writes persistent files into the target project (.ralph/state.json and improvements.json). If you run it on a sensitive or production repository, these files will be created; consider running in a disposable clone or sandboxed environment first. - The tool runs shell commands via execFileSync. Although the commands shown are limited to the project directory (git -- . and grep excludes), ensure you run it against repositories you trust and inspect the code yourself (you have the source included). - There are no network calls or credential requests visible in the provided code, which is good; nonetheless, confirm there are no hidden fetches in any truncated/unseen portions before running on sensitive data. Recommended steps: 1) Run the tool in a disposable clone of the repository to observe behavior and files created. 2) Ensure git, grep, and Node.js are available in the environment, or have the author update the skill manifest to declare those requirements. 3) Review evolve.js and index.js locally (you already have the files) and run the test suite (npm install dev deps, npm test) if you want extra assurance. 4) If you plan to let an agent invoke this autonomously, be aware it will persist state and can run multiple cycles (loop mode); prefer manual invocation or limit the project scope initially. If you want, I can produce a short checklist you can use to safely trial this skill (commands to run in a sandbox, files to inspect after run).
功能分析
Type: OpenClaw Skill Name: ralph-evolver Version: 1.0.6 The OpenClaw AgentSkills skill bundle 'ralph-evolver' is designed for recursive self-improvement of code projects. It uses standard development tools like `git`, `grep`, `npm`, `python`, and `pytest` (via `child_process.execFileSync` in `evolve.js`) to analyze project health, history, and code patterns. All file system and command executions are strictly confined to the target project directory, preventing arbitrary system access or data exfiltration. The `SKILL.md` and the generated prompt in `evolve.js` guide the AI agent to perform code analysis and modifications based on 'first principles' and 'meta-reflection', including the ability to self-modify `evolve.js` itself, which is a core, declared feature of its recursive nature. There is no evidence of malicious intent, unauthorized data access, persistence mechanisms, or obfuscation.
能力评估
Purpose & Capability
The name/description (recursive self-improvement for a codebase) align with the code: it collects git history, TODOs, test/build outputs, and writes improvement/state artifacts. However the package metadata claims 'required binaries: none' while the implementation calls external programs (git and grep) and requires Node.js (package.json specifies node >=18). The omission of those runtime requirements in the manifest is an inconsistency that could mislead users about what the skill actually needs.
Instruction Scope
SKILL.md and the code agree: the tool scans the project (git history, TODO/FIXME comments, test/build outputs), generates prompts, and records improvements. The runtime instructions and code are constrained to the projectPath (exec commands include '--' '.' and grep excludes .git/node_modules), and there are no hidden network endpoints or references to unrelated system configs. It does read repo data and write a .ralph directory in the target project (state and improvements).
Install Mechanism
There is no install spec (instruction-only from the registry perspective) and the repository includes code and package.json. The skill does not fetch arbitrary remote archives or run downloads at install time. Risk is low from an installer standpoint, but users should note it expects to be run with a Node runtime and will write files into the target project on disk.
Credentials
The skill declares no required env vars or credentials (which is appropriate), but it implicitly requires system tools (git, grep) and Node.js that are not declared. That omission can cause surprises: running it in an environment lacking git/grep will fail, and running it in an environment with those tools but on a sensitive repository will expose repository contents to the skill process. No network credentials are requested, which is proportionate to its function.
Persistence & Privilege
The skill persists state and history under a .ralph directory inside the target project and updates a state.json / improvements.json. always:false (no force inclusion) and it doesn't modify other skills or global agent settings. Persisting state in the project directory is legitimate for this tool's purpose but users should be aware it will leave files behind and update iteration counts across runs.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install ralph-evolver
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ralph-evolver 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.6
3 evolution-level improvements + 1 surface fix: - [evolution] Pattern analysis: counts surface/evolution ratio across all history, identifies recurring themes in insights - [evolution] Hypothesis prompts: adds guiding questions after each signal (hotspots, commits, TODOs, errors) to prompt root cause analysis - [surface] Updated SKILL.md documentation to reflect v1.0.5+ features
v1.0.5
First evolution-level improvement: - Added meta-reflection capability with three layers of reflection prompts - Improvement history now asks "surface or evolution?" after listing changes - Recursion section adds meta-questions: "Will this change make evolver better at finding problems?" - Record format now requires level: "surface" | "evolution" classification - This improves the evolver's ability to improve itself, not just fix bugs
v1.0.4
## [1.0.4] - 2025-02-04 ### Added - Positional argument support (can now use 'node index.js .' instead of '--project .') - Python project support to findCoreFiles() (identifies main.py, app.py, etc.) ### Fixed - Converted 2 remaining Chinese comments to English in PromptGenerator.generate()
v1.0.3
Self-iteration rounds 7-9: Added .gitignore to prevent node_modules/, package-lock.json, and state.json from being committed. Added parsePytestResults() method for proper pytest output parsing (was hardcoded 0/1). Fixed empty output edge case - empty string now returns zeros instead of assuming success. Added 3 new tests for pytest parsing (12 tests total).
v1.0.2
Fixed vitest test count parsing (was matching 'Test Files' instead of 'Tests'). Fixed getHotspots() to scope to current directory in monorepo. Fixed TODO/FIXME scanner to filter out self-referential noise.
v1.0.1
## [1.0.1] - 2025-02-04 ### Changed - Converted all output, prompts, comments, and documentation to English for global distribution - Updated SKILL.md description and content to English - Updated help text and CLI messages to English - Updated improvement history format to English
v1.0.0
## [1.0.0] - 2025-02-04 ### 🧬 Ralph-Evolver - Recursive Self-Improvement Engine A project improvement tool based on **Recursion + Emergence + First Principles**. ### Core Philosophy Instead of executing checklists, think from first principles: 1. What is the **essence** of this project? 2. What is it doing that it **shouldn't**? 3. What is it **missing** that it should have? 4. If you **started from scratch**, how would you build it? ### Signal Collection Automatically gathers multi-dimensional context to let insights emerge: - **Code structure** - Class/function signatures, not random truncation - **Commit history** - Understand the "why" behind changes - **TODO/FIXME** - Distress signals in the code - **Error handling patterns** - Find fragile points - **Hotspot files** - Frequent changes = design problems ### Improvement Tracking - Records description, insight, and health metrics for each improvement - Compares before/after effect trends (📈 improved / 📉 degraded / ➡️ unchanged) - History passes to next iteration, avoiding repeated ineffective changes ### Recursive Nature Ralph-Evolver can evolve itself — this is the core of recursion. ### Usage ```bash node index.js --project \u003cpath\u003e # Single iteration node index.js --project \u003cpath\u003e --loop 5 # Run 5 cycles node index.js --project \u003cpath\u003e --task "specific task" ```
元数据
Slug ralph-evolver
版本 1.0.6
许可证
累计安装 14
当前安装数 14
历史版本数 7
常见问题

Ralph Evolver 是什么?

Recursive self-improvement engine. Think from first principles, let insights emerge. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 3714 次。

如何安装 Ralph Evolver?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install ralph-evolver」即可一键安装,无需额外配置。

Ralph Evolver 是免费的吗?

是的,Ralph Evolver 完全免费(开源免费),可自由下载、安装和使用。

Ralph Evolver 支持哪些平台?

Ralph Evolver 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Ralph Evolver?

由 Sky Hai(@hsssgdtc)开发并维护,当前版本 v1.0.6。

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