analyze-results

name	analyze-results
description	分析数模求解结果，计算统计量，生成对比表和洞察。当用户说'分析结果'、'结果对比'、'analyze results'、或需要解读计算结果时使用。
argument-hint	["results-path-or-description"]
allowed-tools	Bash(*), Read, Grep, Glob, Write, Edit, Agent

分析求解结果

Analyze: $ARGUMENTS

Workflow

Step 1: 定位结果文件

Find all relevant result files:

• Check results/, output/, figures/, or project-specific output directories
• Parse JSON/CSV/Excel results into structured data
• Read solver logs for convergence information

Step 2: 构建对比表

Organize results by:

• 子问题: which sub-problem each result belongs to
• 方法: which mathematical method was used
• 关键指标: R², RMSE, 目标函数值, 残差, 误差率 etc.
• 与预期对比: compare against expected values, theoretical bounds, or baseline methods

Step 3: 统计分析

• If multiple runs: report mean +/- std, check robustness
• If sweeping a parameter: identify sensitivity trends (monotonic, U-shaped, plateau)
• Perform error analysis: residual distribution, prediction vs actual
• Check model fit: R², adjusted R², F-statistic, p-values
• Flag outliers or suspicious results (unreasonable values, non-convergence)

Step 4: 生成洞察

For each finding, structure as:

1. 观察: what the data shows (with numbers)
2. 解读: why this result makes sense (or doesn't)
3. 意义: what this means for the competition problem
4. 下一步: what analysis or improvement would strengthen the result

Step 5: 生成图表建议

Based on the analysis, suggest figures for the paper:

• 拟合曲线 (predicted vs actual)
• 残差分布图
• 灵敏度分析图 (parameter sensitivity)
• 误差随参数变化图
• 结果对比柱状图/表格

Step 6: 更新文档

If findings are significant:

• Propose updates to MODEL_REPORT.md or SOLVE_PLAN.md
• Draft a concise finding statement (1-2 sentences)
• Save analysis to RESULTS_ANALYSIS.md

Output Format

Always include:

1. Raw data table (数值结果)
2. Key findings (numbered, concise)
3. Statistical validation (误差分析、模型检验)
4. Suggested figures for paper
5. Suggested next steps (if any)