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在 OpenClaw 中安装
/install deep-loop-thinker
功能描述
多轮深度思考技能。借鉴OpenMythos循环推理架构，每次循环都注入新输入，逐轮深化理解。适用于重要决策、复杂问题、创意生成、问题发现。
使用说明 (SKILL.md)
Deep Loop Thinker Skill v2.1
核心原理
借鉴OpenMythos的Recurrent-Depth Transformer：
- 同一层多次运行，每次有新输入注入
- 隐藏状态h_t更新：
h_{t+1} = A·h_t + B·e + Transformer(h_t, e) - 每次循环不是重复，而是递进
用户需求追踪
谁会使用这个技能？
- 创业者做重大决策
- 分析师处理复杂问题
- 开发者解决技术难题
- 研究者探索未知领域
- AI Agent增强推理能力
用户痛点
- 决策前思考不够全面
- 容易忽视风险
- 缺乏系统性反思
- 决策后不复盘
循环架构
问题输入
↓
[Prelude层] — 提取关键要素
↓
[Recurrent Block] — 多轮递进思考
↑____↓
↓ (每轮注入新洞察)
[Coda层] — 综合输出
↓
行动计划 + 自我反思
多轮思考模式
| 轮次 | 思考类型 | 核心问题 |
|---|---|---|
| 1 | 直觉捕捉 | 第一反应？情绪？ |
| 2 | 利益分析 | 谁受益？谁受损？ |
| 3 | 风险挖掘 | 最坏情况？3年后还重要吗？ |
| 4 | 本质洞察 | 根本原因？规律？ |
| 5 | 行动设计 | 第一步？Plan B？ |
| 6 | 反思验证 | 假设可靠？盲点在哪？ |
用户反馈收集
每次使用后记录：
【用户反馈】
- 用户是谁：{匿名/具体描述}
- 帮助程度：{1-5星}
- 改进建议：{用户的具体反馈}
- 下次需要：{用户的实际问题}
迭代记录
| 版本 | 日期 | 更新内容 |
|---|---|---|
| 1.0 | 2026-04-21 | 初始版本 |
| 2.0 | 2026-04-22 | 增加6轮思考 |
| 2.1 | 2026-04-22 | 增加用户追踪机制 |
质量标准
好的思考报告：
- ✅ 有具体数据/例子支撑
- ✅ 能回答"为什么"
- ✅ 第一步可立即执行
- ✅ 包含风险预案
- ✅ 诚实承认盲点
触发条件
- 问题影响超过3个月
- 涉及多方利益
- 情绪波动明显
- 反复纠结无法决定
- 问题反复出现
约束
- 简单问题不要过度思考（杀鸡不用牛刀）
- 不要超过6轮（防止无限循环）
- 保持诚实，不要自欺欺人
- 行动比完美计划重要
- 记录用户反馈用于迭代
安全使用建议
This skill appears coherent and low-risk: it runs a local Python script that prints structured multi-round prompts and requires no network access or credentials. Before installing or giving it execution rights, you may want to: (1) run the Python script locally to verify behavior, (2) confirm the SKILL.md/README expectations about recording feedback (the shipped script does not persist logs), and (3) ensure you trust the source since the package contains a code file even though it is small and benign. If you plan to let an agent invoke skills autonomously, remember autonomous invocation is platform-default — consider limiting that capability if you do not want skills to run without explicit approvals.
功能分析
Type: OpenClaw Skill
Name: deep-loop-thinker
Version: 2.1.0
The skill is a structured reasoning framework designed to help an AI agent perform multi-round deep thinking. The Python script (deep_loop_thinker.py) is a simple utility that prints conceptual prompts for different stages of analysis, and the documentation (SKILL.md) provides a logical roadmap for the agent to follow. There is no evidence of network activity, file system manipulation, data exfiltration, or malicious prompt injection.
能力评估
Purpose & Capability
Name/description (multi-round reasoning) matches the SKILL.md and the included Python script: both implement prompts and a looped thinking workflow. No unrelated binaries, credentials, or external services are requested.
Instruction Scope
SKILL.md describes workflow, triggers, and a user-feedback recording format. The included Python script implements the interactive multi-round prompts and printing only. There is a minor inconsistency: SKILL.md states that user feedback is recorded for iteration, but the script does not persist feedback to disk or transmit it anywhere — it only prints. This is a functional mismatch but not a security concern.
Install Mechanism
No install spec is present (instruction-only). The only code file is a small local Python script that runs interactively; nothing is downloaded or executed from third-party URLs.
Credentials
The skill requires no environment variables, credentials, or config paths. The code does not access environment variables, secret names, or external services.
Persistence & Privilege
The skill is not always-enabled and uses normal agent invocation settings. It does not modify other skills or system-wide configs and does not persist data or install agents/services.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install deep-loop-thinker - 安装完成后，直接呼叫该 Skill 的名称或使用
/deep-loop-thinker触发 - 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
v2.1.0
增加用户追踪机制和反馈收集
v1.0.0
Initial release of deep-loop-thinker, a multi-turn deep thinking skill inspired by the OpenMythos recurrent reasoning framework.
- Supports multi-round reasoning with new input injected each iteration for deeper understanding.
- Provides structured templates for problem analysis, including intuition, stakeholder interests, risk, essence, action steps, and reflection.
- Tailors reasoning depth to problem complexity (1–6 rounds).
- Ideal for important decisions, complex issues, creative ideation, and root cause discovery.
- Encourages actionable insights, honesty about uncertainty, and risk mitigation in the output.
元数据
常见问题
Deep Loop Thinker 是什么？
多轮深度思考技能。借鉴OpenMythos循环推理架构，每次循环都注入新输入，逐轮深化理解。适用于重要决策、复杂问题、创意生成、问题发现。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 93 次。
如何安装 Deep Loop Thinker？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install deep-loop-thinker」即可一键安装，无需额外配置。
Deep Loop Thinker 是免费的吗？
是的，Deep Loop Thinker 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Deep Loop Thinker 支持哪些平台？
Deep Loop Thinker 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 Deep Loop Thinker？
由 jaxint（@jaxint）开发并维护，当前版本 v2.1.0。
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