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bderiel

open-ralph

作者 Bderiel · GitHub ↗ · v1.0.0
cross-platform ✓ 安全检测通过
1849
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1
当前安装
1
版本数
在 OpenClaw 中安装
/install open-ralph
功能描述
Run an autonomous Open Ralph Wiggum coding loop using OpenCode Zen with free models and automatic fallback.
使用说明 (SKILL.md)

\r \r

What this skill does\r

\r This skill runs an autonomous Ralph Wiggum coding loop using the ralph CLI with OpenCode as the agent provider.\r \r It repeatedly executes the same coding prompt until:\r \r

  • The success criteria are met, OR\r
  • The completion promise is printed, OR\r
  • Max iterations are reached\r \r The loop is optimized for free OpenCode Zen models and includes a fallback chain in case models are rate-limited, disabled, or removed.\r \r ---\r \r

When to use\r

\r Use this skill when you want autonomous coding execution such as:\r \r

  • Fixing failing tests\r
  • Implementing scoped features\r
  • Refactoring codebases\r
  • Resolving lint/type errors\r
  • Running build-fix loops\r
  • Multi-iteration debugging\r \r You MUST be inside a git repository before running Ralph.\r \r ---\r \r

Free model fallback order\r

\r Always attempt models in this order:\r \r

  1. opencode/kimi-k2.5-free ← Best coding performance (limited time free)\r
  2. opencode/minimax-m2.1-free\r
  3. opencode/glm-4.7-free\r
  4. opencode/big-pickle ← Free stealth model fallback\r \r If a model fails due to availability or quota, immediately retry using the next model without changing the prompt or loop parameters.\r \r

Failure triggers for fallback\r

\r Fallback if you encounter errors like:\r \r

  • model disabled\r
  • model not found\r
  • insufficient quota\r
  • quota exceeded\r
  • payment required\r
  • rate limit\r
  • provider unavailable\r \r ---\r \r

How to run the loop\r

\r

Attempt #1 (primary model)\r

\r Run:\r \r ralph "\x3CTASK PROMPT>\r \r Success criteria:\r \r

  • \x3Clist verifiable checks>\r
  • Build passes\r
  • Tests pass\r \r Completion promise:\r \x3Cpromise>COMPLETE\x3C/promise>" \r --agent opencode \r --model opencode/kimi-k2.5-free \r --completion-promise "COMPLETE" \r --max-iterations 20\r \r ---\r \r

Attempt #2 (fallback)\r

\r If attempt #1 fails due to model issues, rerun with:\r \r --model opencode/minimax-m2.1-free\r \r ---\r \r

Attempt #3 (fallback)\r

\r If attempt #2 fails:\r \r --model opencode/glm-4.7-free\r \r ---\r \r

Attempt #4 (final fallback)\r

\r If attempt #3 fails:\r \r --model opencode/big-pickle\r \r ---\r \r

Tasks mode (for large projects)\r

\r For multi-step execution:\r \r ralph "\x3CBIG TASK PROMPT>" \r --agent opencode \r --model opencode/kimi-k2.5-free \r --tasks \r --max-iterations 50\r \r Fallback model order still applies.\r \r ---\r \r

Plugin troubleshooting\r

\r If OpenCode plugins interfere with loop execution, rerun with:\r \r --no-plugins\r \r ---\r \r

Sanity check available Zen models\r

\r If free model availability changes, check:\r \r https://opencode.ai/zen/v1/models\r \r Update fallback order if needed.\r \r ---\r \r

Safety notes\r

\r

  • Always run inside a git repo\r
  • Set iteration limits to avoid runaway loops\r
  • Ensure prompts contain verifiable success criteria\r
  • Review diffs before merging autonomous changes\r \r ---\r \r

Example usage\r

\r Fix failing TypeScript errors:\r \r ralph "Fix all TypeScript errors in the repo.\r \r Success criteria:\r \r

  • tsc passes\r
  • Build succeeds\r \r Completion promise:\r \x3Cpromise>COMPLETE\x3C/promise>" \r --agent opencode \r --model opencode/kimi-k2.5-free \r --completion-promise "COMPLETE" \r --max-iterations 20\r
安全使用建议
This skill appears to do what it says: run the ralph CLI in a loop against OpenCode models. Before installing or running it: (1) ensure you have the ralph and git binaries (and opencode if your setup requires it); (2) confirm whether your OpenCode/Zen setup requires API keys or local auth (the SKILL.md doesn't document credentials) and only provide those you trust; (3) run it on a feature branch or a disposable clone so automated edits don't affect mainline unexpectedly; (4) keep max-iterations small at first and review diffs/commits before merging; (5) verify the model identifiers and the referenced GitHub homepage yourself (the registry metadata left homepage empty while SKILL.md points to a repo) to ensure the project is the expected source.
功能分析
Type: OpenClaw Skill Name: open-ralph Version: 1.0.0 The skill orchestrates an autonomous coding loop using the `ralph` CLI tool with `opencode` as the agent provider. It requires `opencode`, `ralph`, and `git` binaries, which are used to modify code within the current directory. The `SKILL.md` file provides instructions to the OpenClaw agent on how to execute the `ralph` command with various models and fallback logic. There is no evidence of data exfiltration, malicious execution, persistence, or obfuscation. The instructions to the agent are focused on the legitimate operational logic of the skill, not on subverting the agent's purpose or performing unauthorized actions. While the skill enables powerful code modification capabilities, this is its stated purpose, and it includes 'Safety notes' for responsible usage.
能力评估
Purpose & Capability
The name/description describe running an autonomous ralph coding loop using OpenCode models; the declared required binaries (ralph, git, opencode) broadly match that purpose. Minor note: the SKILL.md never invokes an opencode binary directly (it calls ralph with --agent opencode), so requiring a separate opencode executable may be unnecessary but is not strongly inconsistent. The SKILL.md includes a homepage URL, while registry metadata shows none — minor metadata mismatch.
Instruction Scope
The instructions are narrowly scoped to running the ralph CLI with specific models and fallbacks, require being inside a git repo, and advise safe practices (iteration limits, review diffs). They do not instruct reading unrelated files or environment variables. Note: the skill assumes the agent/system can run the ralph CLI which will perform code changes locally — the user should expect code edits/commits and explicitly review them before merging.
Install Mechanism
This is instruction-only with no install spec or archives to download, which minimizes install-time risk. No external packages or executable downloads are specified in the skill itself.
Credentials
The skill declares no required environment variables or credentials, which is coherent with the SKILL.md. However, in practice accessing OpenCode models may require API credentials or local opencode/ralph configuration (not documented in the SKILL.md). The skill does not request unrelated secrets.
Persistence & Privilege
always is false and disable-model-invocation is unset (normal). The skill does not request persistent system privileges or to modify other skills/configs. Autonomous invocation can change repo content via ralph, which is expected behavior for this skill type.
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 open-ralph
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /open-ralph 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
v1.0.0
- Initial release of open-ralph skill. - Enables an autonomous Ralph Wiggum coding loop using OpenCode Zen and the ralph CLI. - Optimized for free OpenCode Zen models with automatic fallback based on model availability and errors. - Supports use cases like fixing tests, implementing features, refactoring, lint/type error fixes, and build-fix loops. - Includes clear usage instructions and example commands. - Requires running inside a git repository.
元数据
Slug open-ralph
版本 1.0.0
许可证
累计安装 1
当前安装数 1
历史版本数 1
常见问题

open-ralph 是什么?

Run an autonomous Open Ralph Wiggum coding loop using OpenCode Zen with free models and automatic fallback. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 1849 次。

如何安装 open-ralph?

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

open-ralph 是免费的吗?

是的,open-ralph 完全免费(开源免费),可自由下载、安装和使用。

open-ralph 支持哪些平台?

open-ralph 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 open-ralph?

由 Bderiel(@bderiel)开发并维护,当前版本 v1.0.0。

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