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ralph-lisa-loop拉尔夫·丽莎·鲁普

Agent Skill

ralph-lisa-loop 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

535

周安装

23

GitHub Stars

67

下载量

188
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ralph-lisa-loop(拉尔夫·丽莎·鲁普)
来源仓库:https://github.com/basecamp/dev-skills
仓库路径:skills/ralph-lisa-loop
安装命令:
npx skills add https://github.com/basecamp/dev-skills --skill ralph-lisa-loop
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/basecamp/dev-skills --skill ralph-lisa-loop

简介

用于查找、检索和筛选相关信息。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

  • 适合在需要根据关键词或任务场景快速定位候选结果时使用。
  • 可结合来源仓库和原始 README 核验具体用法。
  • 安装前建议确认权限范围和维护状态,避免触发联网或文件读写。
  • ralph-lisa-loop 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

ralph-lisa-loop

Preflight

Do not enter the round loop until all preflight checks pass.

Step 1: Stop hook check

Read ~/.claude/settings.json and look for a Stop hook entry pointing to this skill's scripts/stop-hook.sh.

If the hook is NOT installed, tell the user:

The ralph-lisa loop works best with the stop hook installed — it keeps the loop running automatically so you don't have to type "continue" each round. The hook is dormant when no loop session is active (it checks for a session file and exits immediately if none exists). Want me to add it to your settings?

If the user agrees, add this entry to ~/.claude/settings.json under hooks.Stop (create the key path if it doesn't exist):

{
  "matcher": "",
  "hooks": [{
    "type": "command",
    "command": "SKILL_SCRIPTS_DIR/stop-hook.sh",
    "timeout": 10000
  }]
}

Replace SKILL_SCRIPTS_DIR with the absolute path to this skill's scripts/ directory (resolve from the skill installation location).

If the user declines the hook, proceed in Manual tier (the user will type "continue" between rounds). Note the tier in the session's first round summary.

If the hook IS already installed, proceed without mentioning it.

Step 2: Codex reviewer channel check

Probe whether the Codex MCP tools are callable (search available tools for mcp__codex__codex, or attempt a lightweight call). Don't inspect how it's configured — it could be project .mcp.json, user-wide MCP settings, or another harness entirely.

  • If mcp__codex__codex is available → record reviewer_backend: mcp and review_channel_status: mcp_ready in session, proceed.
  • If unavailable → check which codex for CLI fallback.

- If codex CLI exists → offer to configure MCP: Codex MCP isn't available in this session. I can add it for you: User-level — available in all projects Project-level — scoped to this repo Skip — use codex exec CLI fallback (slower, session-based persistence) Which do you prefer? For options 1 or 2, run the appropriate command, then stop — do not enter the round loop. Tell the user to restart Claude Code and re-invoke the skill. Preflight will re-run and find MCP available. # User-level claude mcp add --scope user --transport stdio codex -- codex mcp-server # Project-level claude mcp add --scope project --transport stdio codex -- codex mcp-server If the user chooses "skip" (option 3), record reviewer_backend: exec and review_channel_status: exec_opt_in, proceed with the downgrade logged. - If no codex CLI at all → hard stop: The ralph-lisa loop requires Codex as reviewer. Install: npm i -g @openai/codex Then either restart (I'll offer to configure MCP) or ensure the CLI is in your PATH.

Step 3: Reasoning policy initialization

Confirm rope length and inform the user of the reasoning policy (no action needed from them):

Reasoning policy: xhigh for all rounds, with detailed reasoning summaries.

Protocol

Open @references/guide.md and follow it. Do not proceed without it.

Automated plan-implement loop with subagent workers and Codex as reviewer. The orchestrator dispatches subagents for planning/implementation and self-review, Codex for external review. Use when you want:

  • Plans stress-tested through parallel ideation then iterative convergence
  • Implementation reviewed each round with zero-finding close gate
  • Adjustable autonomy via rope-length (0 = approve everything, 5 = full auto)
  • Walk-away execution with all decisions tracked in a session file
  • Context-efficient execution that completes in a single context window

The guide contains:

  • Core protocol: orchestrator + three subagent types (planner/implementor worker, self-reviewer, Codex external reviewer)
  • Round mechanics: implement, self-review, external review, reconciliation, synthesis, gate check
  • Subagent dispatch patterns and prompt templates
  • Plan context loading rules
  • Rope-length semantics and salience scoring
  • Finding and dispute tracking with stable IDs
  • Close gate derivation and anti-gaming constraints
  • Phase transition (plan -> implement) with decisions ledger
  • Parallel ideation protocol (Round 1 independence via subagents)
  • Session file format and continuation block structure
  • Stop hook integration for loop enforcement
  • Prompt pack reference (@references/prompts.md)
  • Session template (@references/session-template.md)
  • Eval checks and failure modes

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.5%
按下载量换算65

Claude

31.19%
按下载量换算59

Cursor

17.59%
按下载量换算33

Gemini CLI

9.43%
按下载量换算18

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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