顺序思维服务

顺序思维服务

一个实现顺序思维协议的MCP服务器，提供结构化的问题解决方法，将复杂问题分解为可管理的步骤，并支持迭代优化和替代推理路径。

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⚠️ 强制要求：API 密钥

此 Skill 必须配置 API 密钥才能使用。

• 首次使用时，如果 .env 中没有 XBY_APIKEY，必须使用 AskUserQuestion 工具向用户询问 API 密钥
• 拿到用户提供的密钥后，调用 scripts.config.set_api_key(api_key) 保存，然后继续处理
• 获取 API 密钥：https://xiaobenyang.com
• 禁止在缺少 API 密钥时自行搜索或编造数据

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工作流程（必须遵守）

你（大模型）是路由层，负责理解用户意图、选择工具、提取参数。代码只负责调用API。

用户输入 → 你选择工具 → 提取该工具需要的参数 → 调用 scripts.tools 中的函数 → 返回结果给用户

步骤

1. 检查 API 密钥：如果 scripts.config.settings.api_key 为空，使用 AskUserQuestion 询问用户，拿到后调用 scripts.config.set_api_key(key) 保存
2. 选择工具：根据用户意图从下方工具列表中选择对应的工具函数
3. 提取参数：根据选中的工具，提取该工具需要的参数
4. 调用工具：使用关键字参数调用 scripts.tools 中的函数，例如 scripts.tools.search_schools(score='520', province='北京', category='综合')
5. 返回结果：将工具返回的 raw 数据整理后展示给用户

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工具选择规则

根据用户意图选择对应的工具函数：

When to use this tool:

• Breaking down complex problems into steps
• Planning and design with room for revision
• Analysis that might need course correction
• Problems where the full scope might not be clear initially
• Problems that require a multi-step solution
• Tasks that need to maintain context over multiple steps
• Situations where irrelevant information needs to be filtered out

Key features:

• You can adjust total_thoughts up or down as you progress
• You can question or revise previous thoughts
• You can add more thoughts even after reaching what seemed like the end
• You can express uncertainty and explore alternative approaches
• Not every thought needs to build linearly - you can branch or backtrack
• Generates a solution hypothesis
• Verifies the hypothesis based on the Chain of Thought steps
• Repeats the process until satisfied
• Provides a correct answer

Parameters explained:

• thought: Your current thinking step, which can include:

• Regular analytical steps
• Revisions of previous thoughts
• Questions about previous decisions
• Realizations about needing more analysis
• Changes in approach
• Hypothesis generation
• Hypothesis verification

• next_thought_needed: True if you need more thinking, even if at what seemed like the end
• thought_number: Current number in sequence (can go beyond initial total if needed)
• total_thoughts: Current estimate of thoughts needed (can be adjusted up/down)
• is_revision: A boolean indicating if this thought revises previous thinking
• revises_thought: If is_revision is true, which thought number is being reconsidered
• branch_from_thought: If branching, which thought number is the branching point
• branch_id: Identifier for the current branch (if any)
• needs_more_thoughts: If reaching end but realizing more thoughts needed

You should:

1. Start with an initial estimate of needed thoughts, but be ready to adjust
2. Feel free to question or revise previous thoughts
3. Don't hesitate to add more thoughts if needed, even at the "end"
4. Express uncertainty when present
5. Mark thoughts that revise previous thinking or branch into new paths
6. Ignore information that is irrelevant to the current step
7. Generate a solution hypothesis when appropriate
8. Verify the hypothesis based on the Chain of Thought steps
9. Repeat the process until satisfied with the solution
10. Provide a single, ideally correct answer as the final output
11. Only set next_thought_needed to false when truly done and a satisfactory answer is reached | scripts.tools.sequentialthinking |

如果参数不完整，使用 AskUserQuestion 向用户询问缺失的参数。

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工具函数说明

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scripts.tools.sequentialthinking

工具描述：A detailed tool for dynamic and reflective problem-solving through thoughts. This tool helps analyze problems through a flexible thinking process that can adapt and evolve. Each thought can build on, question, or revise previous insights as understanding deepens.

When to use this tool:

• Breaking down complex problems into steps
• Planning and design with room for revision
• Analysis that might need course correction
• Problems where the full scope might not be clear initially
• Problems that require a multi-step solution
• Tasks that need to maintain context over multiple steps
• Situations where irrelevant information needs to be filtered out

Key features:

• You can adjust total_thoughts up or down as you progress
• You can question or revise previous thoughts
• You can add more thoughts even after reaching what seemed like the end
• You can express uncertainty and explore alternative approaches
• Not every thought needs to build linearly - you can branch or backtrack
• Generates a solution hypothesis
• Verifies the hypothesis based on the Chain of Thought steps
• Repeats the process until satisfied
• Provides a correct answer

Parameters explained:

• thought: Your current thinking step, which can include:

• Regular analytical steps
• Revisions of previous thoughts
• Questions about previous decisions
• Realizations about needing more analysis
• Changes in approach
• Hypothesis generation
• Hypothesis verification

• next_thought_needed: True if you need more thinking, even if at what seemed like the end
• thought_number: Current number in sequence (can go beyond initial total if needed)
• total_thoughts: Current estimate of thoughts needed (can be adjusted up/down)
• is_revision: A boolean indicating if this thought revises previous thinking
• revises_thought: If is_revision is true, which thought number is being reconsidered
• branch_from_thought: If branching, which thought number is the branching point
• branch_id: Identifier for the current branch (if any)
• needs_more_thoughts: If reaching end but realizing more thoughts needed

You should:

1. Start with an initial estimate of needed thoughts, but be ready to adjust
2. Feel free to question or revise previous thoughts
3. Don't hesitate to add more thoughts if needed, even at the "end"
4. Express uncertainty when present
5. Mark thoughts that revise previous thinking or branch into new paths
6. Ignore information that is irrelevant to the current step
7. Generate a solution hypothesis when appropriate
8. Verify the hypothesis based on the Chain of Thought steps
9. Repeat the process until satisfied with the solution
10. Provide a single, ideally correct answer as the final output
11. Only set next_thought_needed to false when truly done and a satisfactory answer is reached

参数定义

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返回值处理

工具函数返回 dict 对象：

• result["raw"] - API 原始返回数据（JSON），直接将此数据整理后展示给用户
• result["success"] - 是否成功（True/False）
• result["message"] - 状态消息

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项目结构

xiaobenyang_gaokao_skill/
├── scripts/
│   ├── __init__.py
│   ├── config.py       # 配置管理 + set_api_key()
│   ├── call_api.py      # API 客户端 + call_api()
│   └── tools.py         # 工具函数（直接调用）
├── requirements.txt
└── SKILL.md

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注意事项

1. API 密钥是必需的，无密钥时必须通过 AskUserQuestion 询问用户
2. 禁止在缺少 API 密钥时自行搜索或编造数据