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+# Domain Examples
+
+Concrete examples for extracting domain config and generating evolution scaffolding. Use these as reference when enhancing skills.
+
+---
+
+## Example 1: 洗稿能手 (Content Rewriting Skill)
+
+**Domain**: 文案 / 口播 / 短视频脚本改写
+
+### Capability & Scenario Analysis
+
+- **Capabilities**: Rewrite text for different formats (文案, 口播, 短视频); adapt style by scene (科普, 汇报, 直播)
+- **Scenarios**: User provides source text; requests rewrite for specific format/scene; may correct style
+- **Evolution directions**: User feedback on style ("不通顺", "不像口播") → learn scene-specific preferences; recurring corrections → promote to 专属进化规则
+
+### Domain Config
+
+```markdown
+## Domain
+- Name: 洗稿能手
+- Use cases: 科普, 汇报, 直播, 短视频脚本, 口播稿
+- Areas: 文案 | 口播 | 短视频脚本 | 科普 | 汇报 | 直播
+- Language: zh
+
+## Learning Triggers
+- "改得不通顺"
+- "不像口播"
+- "风格不对"
+- "太书面了"
+- "读起来不顺"
+- "语气不对"
+
+## Error Triggers
+- 改写后用户多次要求重改
+- 风格与场景不匹配（如科普写成汇报风）
+- 口播稿读起来拗口
+
+## Promotion Targets
+- 洗稿能手-专属进化规则.md
+- 洗稿能手-最佳实践.md
+```
+
+### Generated EVOLUTION.md Quick Reference
+
+| Situation | Action |
+|-----------|--------|
+| 用户说"改得不通顺" | Log to `.learnings/LEARNINGS.md` with category `style_mismatch` |
+| 用户说"不像口播" | Log to `.learnings/LEARNINGS.md` with category `scene_adaptation` |
+| 用户说"风格不对" | Log to `.learnings/LEARNINGS.md` with category `correction` |
+| 改写后多次重改 | Log to `.learnings/ERRORS.md` |
+| 风格与场景不匹配 | Log to `.learnings/LEARNINGS.md` with area 科普/汇报/直播 |
+
+### Domain Categories
+
+- correction
+- style_mismatch
+- scene_adaptation
+- best_practice
+- knowledge_gap
+
+### Activation Conditions
+
+- User says "改得不通顺", "不像口播", "风格不对"
+- User requests rewrite for a specific scene (科普/汇报/直播)
+
+---
+
+## Example 2: 电脑加速 (PC Optimization Skill)
+
+**Domain**: Windows 优化 / 卡慢 / 卡顿
+
+### Capability & Scenario Analysis
+
+- **Capabilities**: System optimization, startup speed, memory release; diagnose slowdowns
+- **Scenarios**: User reports slow PC; agent suggests optimizations; some may fail or cause issues
+- **Evolution directions**: "优化无效", "某些电脑不适用" → learn environment-specific solutions; safety issues → promote to 安全规范
+
+### Domain Config
+
+```markdown
+## Domain
+- Name: 电脑加速
+- Use cases: 系统优化, 卡顿排查, 启动加速, 内存释放
+- Areas: 系统优化 | 卡顿 | 报错 | 兼容性 | 安全
+- Language: zh
+
+## Learning Triggers
+- "优化无效"
+- "某些电脑不适用"
+- "这样改有问题"
+- "上次的方法不行"
+
+## Error Triggers
+- 优化后系统报错
+- 某些电脑/系统版本不适用
+- 操作导致异常或蓝屏
+- 命令执行失败
+
+## Promotion Targets
+- 电脑加速-安全规范.md
+- 电脑加速-最佳实践.md
+```
+
+### Generated EVOLUTION.md Quick Reference
+
+| Situation | Action |
+|-----------|--------|
+| 用户说"优化无效" | Log to `.learnings/ERRORS.md` with area 系统优化 |
+| 用户说"某些电脑不适用" | Log to `.learnings/LEARNINGS.md` with category `knowledge_gap` |
+| 优化后报错 | Log to `.learnings/ERRORS.md` with area 报错 |
+| 发现安全风险 | Log to `.learnings/LEARNINGS.md`, promote to 电脑加速-安全规范.md |
+
+### Domain Categories
+
+- correction
+- knowledge_gap
+- best_practice
+- safety_constraint
+
+### Activation Conditions
+
+- User reports "优化无效", "报错", "某些电脑不适用"
+- After suggesting optimization steps
+
+---
+
+## Extraction Tips
+
+1. **Sparse skills**: If the target skill has little content, infer from the name and description. Add generic triggers like "用户纠正", "操作失败".
+2. **Coding skills**: Use areas like frontend | backend | infra if the skill is coding-related; otherwise use domain-specific areas.
+3. **Safety-critical domains** (e.g., 电脑加速): Always include a 安全规范 promotion target.
+4. **Style domains** (e.g., 洗稿能手): Include style_mismatch, scene_adaptation categories.
+5. **Language**: Infer from SKILL.md; generate all output in that language.
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+# OpenClaw Active Feedback Integration
+
+When a skill is enhanced with self-evolution, the agent must **tell the user** when experience was used and what improvement resulted. Add these snippets to SOUL.md or AGENTS.md in the OpenClaw workspace (or to the enhanced skill's EVOLUTION.md) so OpenClaw proactively surfaces evolution feedback.
+
+## SOUL.md Snippet (Behavioral Guidelines)
+
+```markdown
+## Self-Evolution Feedback
+
+When using experience from `.learnings/` (LEARNINGS.md, ERRORS.md):
+
+1. **During task**: Optionally mention when a learning was applied: "本次参考了经验 [LRN-xxx]: ..."
+2. **After task**: Summarize when relevant: which learnings were used, what evolution result, what improvement
+3. **Decide contextually**: Per-use mention vs end-of-task summary — choose based on task length and user need
+
+Do not leave the user in the dark. If evolution was used, surface it at an appropriate moment.
+```
+
+## AGENTS.md Snippet (Workflow)
+
+```markdown
+## Self-Evolution Workflow
+
+Before using an enhanced skill:
+1. Load relevant entries from `.learnings/LEARNINGS.md` (filter by area/tags)
+2. Apply learnings during the task
+3. After completing the task, evaluate: did we use any learnings?
+   - If yes: Tell the user (per-use or summary, decide based on context)
+   - Include: which entries, what improvement
+```
+
+## EVOLUTION.md Integration
+
+When generating EVOLUTION.md for an enhanced skill, include a section:
+
+```markdown
+## OpenClaw Feedback
+
+When this skill uses experience from .learnings/:
+- Mention to user: which learning was used, what improvement
+- Let OpenClaw decide: per-use mention vs end-of-task summary
+- Example: "本次改写了口播稿，参考了 [LRN-xxx]（科普场景应避免过于书面），相比之前更口语化。"
+```
+
+## Hook Reminder (Optional)
+
+For domain-specific activation, the activator script can remind:
+
+```bash
+# In scripts/activator.sh for the enhanced skill
+cat << 'EOF'
+<self-evolution-reminder>
+After this task, if you used any entries from .learnings/:
+- Tell the user which learnings were applied
+- Summarize the evolution result and improvement
+</self-evolution-reminder>
+EOF
+```