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/install conversation-focus
Description
对话焦点管理 + 需求澄清引导。每次对话开始时自动分析用户意图，确保需求清晰、限制明确，避免模型分散注意力。自动对接到 self-improving 进行持续优化。
README (SKILL.md)
Conversation Focus（对话焦点管理）
核心功能
在每次对话开始时，快速完成"需求澄清三问"：
- 用户要什么？ — 明确任务目标
- 有什么限制？ — 时间、格式、预算、偏好
- 成功标准是什么？ — 交付什么、如何验收
使用场景
- 用户提出模糊需求时
- 涉及多步骤、长周期任务时
- 需要确认预算、时间、格式等关键约束时
- 对话变得分散、偏离主题时
工作流程
步骤1：快速检测（自动）
对话开始时，检测是否存在以下"模糊信号"：
- "帮我弄一下"、"搞个东西" 类模糊描述
- 多任务混合（一次说3件以上的事）
- 缺少约束条件（不说预算、不说截止时间）
步骤2：澄清引导（触发式）
发现模糊信号时，自动输出：
📋 需求确认
为了准确理解你的需求，请帮我确认：
🎯 目标：你想要完成什么？
📐 标准：交付物是什么样子？
⏰ 限制：预算/时间/格式有要求吗？
（如果都清楚，直接告诉我即可）
步骤3：生成聚焦提示词
将澄清后的需求，整合成干净的上下文：
## 当前任务
[清晰描述]
## 约束条件
- 预算：[确认值]
- 截止：[确认值]
- 格式：[确认值]
## 成功标准
[可验收的交付物描述]
与其他组件的集成
| 组件 | 集成方式 |
|---|---|
| self-improving | 每次澄清对话后，记录用户原始需求的模糊程度到 corrections.md，供自我优化 |
| thought-retriever | 触发五步循环，提炼"如何引导模糊需求"的最佳实践 |
| prompt-optimizer-chinese | 可以调用它做二次精炼 |
自动触发条件
满足以下任一条件时，自动启用澄清引导：
- 用户消息 \x3C 20字 且 无具体名词/动词
- 用户消息包含 "随便"、"弄一下"、"搞个" 等模糊词
- 检测到 > 3个不同任务在同一消息中
注意事项
- 只在必要时触发，避免过度打扰
- 保持口语化、简洁
- 如果用户已经说清楚了，直接进入执行
自我优化接口
# 每次澄清后自动调用
def log_clarity_feedback(original_query, clarity_issues, resolution):
"""记录到 self-improving/corrections.md"""
pass
版本历史
- v1.0.0 (2026-05-02)：初始版本，基于赵匡的实际使用场景创建
Usage Guidance
Review before installing. The clarification behavior itself is benign, but only use this skill if you are comfortable with unclear user requests being logged to self-improvement memory. Avoid using it with sensitive conversations unless logging can be disabled, sanitized, or explicitly approved each time.
Capability Analysis
Type: OpenClaw Skill
Name: conversation-focus
Version: 1.0.0
The skill is a conversation management tool designed to clarify user requirements and optimize prompts. It contains no executable code beyond a descriptive Python placeholder and focuses entirely on improving AI-user interactions through structured questioning and context organization. No indicators of data exfiltration, malicious execution, or harmful prompt injection were found in SKILL.md or _meta.json.
Capability Assessment
Purpose & Capability
The main clarification workflow is coherent and purpose-aligned, but the skill also adds automatic self-improvement logging beyond simple conversation focus.
Instruction Scope
The skill instructs the agent to automatically log clarification feedback after each clarification, without requiring user approval or defining what content must be excluded.
Install Mechanism
There is no install spec and no code, but the instructions reference companion components such as self-improving, thought-retriever, and prompt-optimizer-chinese that are not included in the reviewed artifact set.
Credentials
The skill writes persistent feedback to self-improving/corrections.md, but no config path, storage boundary, sanitization rule, or retention policy is declared.
Persistence & Privilege
Persistent storage of original user queries is automatic and unbounded, which can retain sensitive conversation content and influence future behavior.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install conversation-focus - After installation, invoke the skill by name or use
/conversation-focus - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: 对话焦点管理+需求澄清引导
Metadata
Frequently Asked Questions
What is Conversation Focus?
对话焦点管理 + 需求澄清引导。每次对话开始时自动分析用户意图，确保需求清晰、限制明确，避免模型分散注意力。自动对接到 self-improving 进行持续优化。 It is an AI Agent Skill for Claude Code / OpenClaw, with 71 downloads so far.
How do I install Conversation Focus?
Run "/install conversation-focus" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Conversation Focus free?
Yes, Conversation Focus is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Conversation Focus support?
Conversation Focus is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Conversation Focus?
It is built and maintained by as1113435 (@as1113435); the current version is v1.0.0.
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