evolution-predictor
/install jpeng-evolution-predictor
Evolution Predictor
Predict optimal next evolution actions based on history analysis.
When to Use
- Determining next evolution focus
- Need to break stagnation cycles
- Planning innovation strategy
- Want proactive evolution guidance
Quick Start
const predictor = require('./skills/evolution-predictor');
// Get prediction for next action
const prediction = predictor.predictNextAction();
console.log(predictor.formatReport(prediction));
// Get recommended skill to create
const skill = predictor.getRecommendedSkill();
console.log('Recommended:', skill.name);
API
predictNextAction(options)
Analyze evolution history and predict optimal next action.
Returns:
prediction: Action recommendation with category, priority, descriptionconfidence: Prediction confidence (0-1)reasoning: List of reasons for the predictionmetrics: Success rate, stagnation level, innovation gap
getRecommendedSkill()
Get a specific skill recommendation based on prediction.
formatReport(prediction)
Generate human-readable prediction report.
Prediction Categories
force_innovate (Critical)
When stagnation level > 60%
- Break stagnation cycles
- Create novel skills
- Implement cross-skill orchestration
prioritize_innovate (High)
When innovation gap > 70%
- Increase innovation rate
- Fill capability gaps
- Address user feature requests
explore_new_domains (Medium)
When success rate > 90%
- Expand capabilities
- Add integrations
- Improve user experience
stabilize (Normal)
Normal operation mode
- Continue current pattern
- Monitor for patterns
- Optimize existing skills
Metrics
- Success Rate: Percentage of recent successful cycles
- Stagnation Level: Based on stagnation signal frequency
- Innovation Gap: How much the system has been optimizing vs innovating
Example Output
🔮 Evolution Predictor
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 Metrics:
Success Rate: 98%
Stagnation Level: 85%
Innovation Gap: 75%
🎯 Prediction:
Action: force_innovate
Category: break_stagnation
Priority: critical
Description: Force innovation to break stagnation cycle
Confidence: 85%
💡 Suggested Skills:
1. Create a novel skill that addresses an unmet need
2. Implement cross-skill orchestration
3. Add predictive capabilities
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install jpeng-evolution-predictor - 安装完成后,直接呼叫该 Skill 的名称或使用
/jpeng-evolution-predictor触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
evolution-predictor 是什么?
Predict optimal next evolution actions based on history analysis, including stagnation detection, innovation gap measurement, and skill recommendations. Use... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 132 次。
如何安装 evolution-predictor?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install jpeng-evolution-predictor」即可一键安装,无需额外配置。
evolution-predictor 是免费的吗?
是的,evolution-predictor 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
evolution-predictor 支持哪些平台?
evolution-predictor 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 evolution-predictor?
由 jpengcheng523-netizen(@jpengcheng523-netizen)开发并维护,当前版本 v1.0.0。