sequential-thinking顺序推理

Structured reasoning through sequential thinking — break complex problems into steps, solve each independently, verify consistency, synthesize conclusions with confidence scoring. Use for complex analysis, debugging, and multi-step reasoning.

作者: admin | 来源: ClawHub

🧩 Sequential Thinking

Structured reasoning through sequential thinking. Break complex problems into logical steps, solve each independently, verify consistency, and synthesize a final answer with a confidence score.

Why Sequential Thinking?

LLMs often rush to conclusions. This skill forces step-by-step decomposition:

1. Decompose — Break the problem into discrete steps
Solve — Address each step independently
Verify — Check consistency between steps
Synthesize — Combine into a final answer with confidence

Usage

CODEBLOCK0

Flags

Flag	Default	Description
INLINECODE0	7	Maximum number of reasoning steps
INLINECODE1

Output Format

CODEBLOCK1

How It Works

1. Decomposition prompt asks the model to identify the key sub-questions
Step-solving prompts address each sub-question with context from prior steps
Verification prompt (optional) checks for contradictions between steps
Synthesis prompt combines all step conclusions into a coherent answer
Confidence scoring based on step agreement, verification results, and hedging language

Credits

Built by M. Abidi | agxntsix.ai YouTube | GitHub Part of the AgxntSix Skill Suite for OpenClaw agents.

📅 Need help setting up OpenClaw for your business? Book a free consultation

🧩 顺序思维

通过顺序思维进行结构化推理。将复杂问题分解为逻辑步骤，独立解决每个步骤，验证一致性，并综合生成带有置信度评分的最终答案。

为什么使用顺序思维？

大语言模型常常急于得出结论。本技能强制进行逐步分解：

1. 分解 — 将问题拆分为离散步骤
解决 — 独立处理每个步骤
验证 — 检查步骤间的一致性
综合 — 合并为带有置信度的最终答案

使用方法

bash

基础顺序推理

python3 {baseDir}/scripts/sequential_think.py 如果月球消失，地球气候会发生什么变化？

限制为5个步骤

python3 {baseDir}/scripts/sequential_think.py 设计一个可容纳100万人的可持续城市 --steps 5

启用自我验证

python3 {baseDir}/scripts/sequential_think.py P=NP是否成立？ --verify

使用特定模型

python3 {baseDir}/scripts/sequential_think.py 解释量子计算 --model anthropic/claude-sonnet-4

JSON输出

python3 {baseDir}/scripts/sequential_think.py 比较React与Vue --json

详细模式（显示所有中间推理过程）

python3 {baseDir}/scripts/sequential_think.py 解决这个逻辑谜题... --verbose

参数标志

标志	默认值	描述
--steps	7	最大推理步骤数
--verify

输出格式

🧩 顺序思维：您的问题
══════════════════════════════════════════

步骤 1/5：[步骤标题]
→ [此步骤的推理和结论]

步骤 2/5：[步骤标题]
→ [此步骤的推理和结论]

...

✅ 验证：[通过/失败 — 一致性说明]

📋 综合：
[最终整合答案]

🎯 置信度：85%（高）

工作原理

1. 分解提示要求模型识别关键子问题
步骤求解提示结合前序步骤的上下文处理每个子问题
验证提示（可选）检查步骤间的矛盾
综合提示将所有步骤结论合并为连贯答案
置信度评分基于步骤一致性、验证结果和模糊措辞

致谢

由 M. Abidi 构建 | agxntsix.ai YouTube | GitHub 属于面向 OpenClaw 智能体的 AgxntSix 技能套件 的一部分。

📅 需要为您的企业设置 OpenClaw？ 预约免费咨询

sequential-thinking顺序推理