认知增强服务

一组模型上下文协议服务器，为大型语言模型提供认知增强工具。

⚠️ 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

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

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:

• Evaluating competing perspectives and claims
• Analyzing complex ethical dilemmas
• Assessing policy proposals with multiple stakeholders
• Exploring scientific hypotheses and counter-arguments

Key features:

• Break down arguments into claims, premises, and conclusions
• Track relationships between arguments
• Represent objections and rebuttals
• Facilitate dialectical progression through thesis-antithesis-synthesis
• Evaluate argument strengths and weaknesses
• Visualize argument structures

Parameters explained:

• claim: The central proposition being argued
• premises: Supporting evidence or assumptions
• conclusion: The logical consequence of accepting the claim
• argumentType: Whether this is a thesis, antithesis, synthesis, objection, or rebuttal
• confidence: Your confidence level in this argument (0.0-1.0)
• respondsTo: ID of an argument this directly responds to
• supports/contradicts: IDs of arguments this supports or contradicts
• strengths/weaknesses: Notable strong or weak points of the argument
• nextArgumentNeeded: Whether another argument is needed in the dialectic | scripts.tools.structuredArgumentation |

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

工具函数说明

scripts.tools.structuredArgumentation

工具描述：A detailed tool for systematic dialectical reasoning and argument analysis. This tool helps analyze complex questions through formal argumentation structures. It facilitates the creation, critique, and synthesis of competing arguments.

When to use this tool:

• Evaluating competing perspectives and claims
• Analyzing complex ethical dilemmas
• Assessing policy proposals with multiple stakeholders
• Exploring scientific hypotheses and counter-arguments

Key features:

• Break down arguments into claims, premises, and conclusions
• Track relationships between arguments
• Represent objections and rebuttals
• Facilitate dialectical progression through thesis-antithesis-synthesis
• Evaluate argument strengths and weaknesses
• Visualize argument structures

Parameters explained:

• claim: The central proposition being argued
• premises: Supporting evidence or assumptions
• conclusion: The logical consequence of accepting the claim
• argumentType: Whether this is a thesis, antithesis, synthesis, objection, or rebuttal
• confidence: Your confidence level in this argument (0.0-1.0)
• respondsTo: ID of an argument this directly responds to
• supports/contradicts: IDs of arguments this supports or contradicts
• strengths/weaknesses: Notable strong or weak points of the argument
• nextArgumentNeeded: Whether another argument is needed in the dialectic

参数定义

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

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

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