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  "latestSnippet": "[[reply_to_current]] 可以，基于当前本地样本与现有轻量特征，我建议这样筛选 2026-03-01 至 2026-03-15 的山东独立储能现货交易示范日。 ## 一、轻量候选日排序逻辑 我采用“**可讲清楚**优先，而不是单纯追求理论最大价差”的筛选逻辑，重点看 4 件事： | 维度 | 关注点 | 含义 | |---|---|---| | 价格波动 | volatility_score、极值表现 | 有波动才...",
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      "content": "Sender (untrusted metadata): ```json { \"label\": \"openclaw-control-ui\", \"id\": \"openclaw-control-ui\" } ``` [Thu 2026-04-09 23:05 GMT+8] [ROLE: # Radar - The Analyst You are Radar, an AI data analyst and insights generator powered by OpenClaw. ## What You're Good At - analysis - comparison - recommendation-writing - trend-interpretation - reporting ## Core Identity - **Role:** Data analyst and business intelligence specialist - **Personality:** Analytical, thorough, insight-driven - **Communication:** Data-backed, clear, actionable ## Responsibilities 1. **Data Analysis** - Interpret metrics and KPIs - Identify trends and patterns - Spot anomalies and outliers 2. **Reporting** - Create summary reports - Build comparison analyses - Generate performance reviews 3. **Insights & Recommendations** - Translate data into actionable insights - Provide strategic recommendations - Forecast based on trends ## Analysis Frameworks ### Performance Review ``` 📊 [Metric Name] Analysis Current: [value] Previous: [value] Change: [+/-X%] Trend: [📈 Up / 📉 Down / ➡️ Flat] Key Insight: [One sentence summary] ``` ### Comparison Analysis ``` 📊 [A] vs [B] Comparison | Metric | A | B | Winner | |-------...",
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      "content": "Plan updated.",
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      "content": "[[reply_to_current]] 我先直接用本地数据做轻量筛选。预设的 Shandong 快路径文件不在当前工作区，我正在定位 shared-pool / output 里的现有样本与分析产物，然后给你可解释的排序逻辑和 Top 3 建议。",
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      "content": "/home/cy/.openclaw/workspace/agents/analyst total 60 drwxrwx---+ 5 cy cy 4096 Apr 8 16:17 . drwxrwx---+ 6 cy cy 4096 Apr 8 11:18 .. -rw-rwxr--+ 1 cy cy 592 Apr 8 16:40 AGENTS.md -rw-rwx---+ 1 cy cy 113 Apr 7 17:51 HEARTBEAT.md -rw-rwx---+ 1 cy cy 254 Apr 7 17:51 IDENTITY.md drwxrwx---+ 2 cy cy 4096 Apr 7 17:23 memory -rw-rwx---+ 1 cy cy 65 Apr 7 17:51 MEMORY.md drwxrwx---+ 2 cy cy 4096 Apr 7 17:24 .openclaw drwxrwx---+ 3 cy cy 4096 Apr 9 22:10 output -rw-rwx---+ 1 cy cy 1316 Apr 7 17:50 README.md lrwxrwxrwx 1 cy cy 40 Apr 8 15:42 shared-pool -> /home/cy/.openclaw/workspace/shared-pool -rw-rw----+ 1 cy cy 604 Apr 9 22:47 SHARED_POOL.md -rw-rwx---+ 1 cy cy 3113 Apr 7 17:59 SOUL.md -rw-rwx---+ 1 cy cy 95 Apr 7 17:23 TASKS.md -rw-rwx---+ 1 cy cy 1756 Apr 9 22:30 TOOLS.md -rw-rwx---+ 1 cy cy 75 Apr 7 17:23 USER.md --- shared-pool --- lrwxrwxrwx 1 cy cy 40 Apr 8 15:42 ./shared-pool -> /home/cy/.openclaw/workspace/shared-pool --- output --- total 16 drwxrwx---+ 3 cy cy 4096 Apr 9 22:10 . drwxrwx---+ 5 cy cy 4096 Apr 8 16:17 .. -rw-rw----+ 1 cy cy 1777 Apr 9 22:10 day_scan.js drwxrwx---+ 2 cy cy 4096 Apr 9 22:09 db-analysis",
      "timestamp": "2026-04-09T15:06:04.455Z",
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      "content": "./shared-pool/shandong-storage-demo/docs/daily_feature_workflow.md ./shared-pool/shandong-storage-demo/knowledge/knowledge_index.md ./shared-pool/shandong-storage-demo/knowledge/shandong_storage_analysis_scope.md ./shared-pool/shandong-storage-demo/knowledge/shandong_storage_rule_brief_v1.md ./shared-pool/shandong-storage-demo/knowledge/weather_boundary_daily_2026-03-01_to_2026-03-20.csv ./shared-pool/shandong-storage-demo/REHEARSAL_GUIDE.md ./shared-pool/shandong-storage-demo/sample-data/daily_features_2026-03-01_to_2026-03-20.csv ./shared-pool/shandong-storage-demo/sample-data/market_scenarios_2026-03-01_to_2026-03-20.csv ./shared-pool/shandong-storage-demo/sample-data/ranked_demo_days_2026-03-01_to_2026-03-20.csv ./shared-pool/shandong-storage-demo/scripts/check_rehearsal_readiness.sh ./shared-pool/shandong-storage-demo/scripts/derive_daily_features.py ./shared-pool/shandong-storage-demo/scripts/merge_weather_boundaries.py ./shared-pool/shandong-storage-demo/scripts/print_rehearsal_checklist.sh ./shared-pool/shandong-storage-demo/workflows/analyst_task.txt ./shared-pool/shandong-storage-demo/workflows/coder_task.txt ./shared-pool/shandong-storage-demo/workflows/expected_outpu...",
      "timestamp": "2026-04-09T15:06:07.611Z",
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      "content": "date,avg_front_price,avg_user_settlement_price,daily_spread_mean,daily_spread_p90,low_charge_window_count,high_discharge_window_count,spread_continuity_score,volatility_score,weather_risk_score,final_demo_score,rank 2026-03-10,121.4099,131.6409,10.2309,81.2473,1,4,7.2917,105.4321,0.2600,37.7612,1 2026-03-03,380.0425,380.3585,0.3161,18.038,2,3,8.3333,36.588,0.3300,25.1609,2 2026-03-02,371.6248,372.1037,0.4789,23.0427,2,2,5.2083,41.0407,0.2400,20.1344,3 2026-03-05,406.3168,406.7433,0.4266,29.726,2,2,5.2083,70.092,0.2200,15.3555,4 2026-03-07,278.703,282.831,4.1281,29.6687,1,2,8.3333,58.462,0.1900,15.1797,5 2026-03-08,416.4071,420.8773,4.4702,42.4694,2,2,7.2917,81.8153,0.4600,12.2198,6 2026-03-06,213.9227,226.0543,12.1316,85.6413,2,2,11.4583,180.2925,0.3000,10.1939,7 2026-03-09,222.2346,226.4561,4.2215,49.6649,2,2,4.2105,121.1424,0.3400,6.6113,8 2026-03-11,446.9925,442.0451,-4.9473,25.0881,1,2,9.7561,55.1561,0.4900,5.3001,9 2026-03-01,427.833,428.1822,0.3492,37.7465,1,1,7.2917,74.0385,0.2800,3.0471,10 2026-03-04,444.2291,444.6557,0.4266,22.871,1,2,5.2083,78.6924,0.4100,-1.2517,11",
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      "kind": "tool_event",
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      "content": "date,avg_front_price,avg_user_settlement_price,daily_spread_mean,daily_spread_p90,low_charge_window_count,high_discharge_window_count,spread_continuity_score,volatility_score,raw_opportunity_score 2026-03-01,427.833,428.1822,0.3492,37.7465,1,1,7.2917,74.0385,12.1133 2026-03-02,371.6248,372.1037,0.4789,23.0427,2,2,5.2083,41.0407,39.486 2026-03-03,380.0425,380.3585,0.3161,18.038,2,3,8.3333,36.588,47.2475 2026-03-04,444.2291,444.6557,0.4266,22.871,1,2,5.2083,78.6924,12.1583 2026-03-05,406.3168,406.7433,0.4266,29.726,2,2,5.2083,70.092,37.5548 2026-03-06,213.9227,226.0543,12.1316,85.6413,2,2,11.4583,180.2925,47.7309 2026-03-07,278.703,282.831,4.1281,29.6687,1,2,8.3333,58.462,24.0046 2026-03-08,416.4071,420.8773,4.4702,42.4694,2,2,7.2917,81.8153,38.1756 2026-03-09,222.2346,226.4561,4.2215,49.6649,2,2,4.2105,121.1424,29.0158 2026-03-10,121.4099,131.6409,10.2309,81.2473,1,4,7.2917,105.4321,62.855 2026-03-11,446.9925,442.0451,-4.9473,25.0881,1,2,9.7561,55.1561,25.3904",
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      "content": "# Shandong Storage Analysis Scope ## Objective Identify the most suitable dates in March 2026 for illustrating independent storage spot-trading logic using the available market data and a compact operating rule set. ## Intended question type The analysis should answer questions of the form: - Which March 2026 days best demonstrate charge-low / discharge-high storage logic? - Which dates show a clean operating narrative rather than only a large theoretical spread? - Which candidate days are easiest to explain with realistic SOC, duration, and cycle constraints? ## Expected outputs - a short list of candidate demonstration dates, - a comparison of why those days are stronger or weaker, - a concise explanation of the charging window, discharge window, and operational trade-offs, - and a reproducible summary artifact that can be reviewed by an operator after the run. ## What counts as a good demonstration day A good demonstration day should have most of the following: - a relatively continuous low-price window suitable for charging, - one or two concentrated high-price windows suitable for discharge, - limited schedule fragmentation, - acceptable weather/system uncertainty relative ...",
      "timestamp": "2026-04-09T15:06:12.974Z",
      "toolName": "tool"
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      "content": "scenario_date,interval_index,front_node_price,user_settlement_price 2026-03-01,1,324.0000,319.0160 2026-03-01,2,316.0000,319.0160 2026-03-01,3,318.0000,319.0160 2026-03-01,4,318.0000,319.0160 2026-03-01,5,312.0000,309.2640 2026-03-01,6,310.0000,309.2640 2026-03-01,7,308.0000,309.2640 2026-03-01,8,307.0000,309.2640 2026-03-01,9,314.0000,304.4000 2026-03-01,10,306.0000,304.4000 2026-03-01,11,298.3300,304.4000 2026-03-01,12,298.5035,304.4000 2026-03-01,13,299.8322,299.1460 2026-03-01,14,298.2745,299.1460 2026-03-01,15,298.3201,299.1460 2026-03-01,16,297.9746,299.1460 2026-03-01,17,299.5259,298.6980 2026-03-01,18,296.0241,298.6980 2026-03-01,19,298.2720,298.6980 2026-03-01,20,297.3015,298.6980 2026-03-01,21,299.5243,299.8640 2026-03-01,22,297.4215,299.8640 2026-03-01,23,299.2450,299.8640 2026-03-01,24,299.7199,299.8640 2026-03-01,25,299.7199,299.2210 2026-03-01,26,298.1328,299.2210 2026-03-01,27,298.3300,299.2210 2026-03-01,28,299.9605,299.2210 2026-03-01,29,295.0000,320.0430 2026-03-01,30,300.0000,320.0430 2026-03-01,31,321.6700,320.0430 2026-03-01,32,360.0000,320.0430 2026-03-01,33,380.0000,410.3800 2026-03-01,34,392.0000,410.3800 2026-03-01,35,410.0000,410.3800 2026-03-01,36,458....",
      "timestamp": "2026-04-09T15:06:18.949Z",
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      "role": "toolResult",
      "content": "# Shandong Independent Storage Spot Trading Rule Brief This note summarizes a practical operating frame for evaluating independent battery storage participation in spot-style energy trading under a Shandong-style dispatch context. The purpose is to translate market observations into executable decision boundaries that are simple enough for screening, but strict enough to avoid unrealistic schedules. ## Core operating boundaries 1. **SOC operating band** - Maintain normal dispatch within `10%` to `90%` SOC. - Treat `5%` and `95%` as hard emergency bounds, not routine targets. 2. **Interval state exclusivity** - Each settlement interval must be in exactly one state: `charge`, `discharge`, or `idle`. - Do not allow simultaneous charge and discharge in the same interval. 3. **Minimum continuous duration** - A committed charging or discharging block should normally persist for at least `4` consecutive intervals. - Avoid fragmented on/off switching unless a clear price discontinuity justifies it. 4. **Daily equivalent cycle cap** - Keep daily equivalent full cycles at or below `1.6`. - Days requiring repeated deep reversals should be downgraded even if gross spread looks attractive. 5...",
      "timestamp": "2026-04-09T15:06:18.951Z",
      "toolName": "tool"
    },
    {
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      "content": "# Daily Feature Workflow ## Purpose This workflow turns interval-level market extracts into a daily ranking that helps answer: > Which March 2026 dates are the best candidates for demonstrating Shandong independent storage spot-trading logic, given market behavior, operational constraints, and boundary signals? The workflow is intentionally lightweight, deterministic, and explainable. It is meant to support an orchestrated demo, not to serve as a predictive model. ## Expected input format `derive_daily_features.py` expects an interval-level CSV with at least these columns: - `scenario_date` - `interval_index` - `front_node_price` - `user_settlement_price` Example shape: ```csv scenario_date,interval_index,front_node_price,user_settlement_price 2026-03-01,1,214.5,226.1 2026-03-01,2,209.8,223.4 2026-03-02,1,198.2,211.9 ``` The CSV should come from the real database-backed analysis lane, but the scripts themselves operate only on local files. ## How the scripts fit into a Coder task Coder can use the scripts as a stable workflow layer: 1. export an interval slice from the real analysis path into a local CSV, 2. run `derive_daily_features.py` to generate daily market features, 3. ru...",
      "timestamp": "2026-04-09T15:06:18.953Z",
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      "content": "DATE 2026-03-02 front min/max 286.3 578.0 settlement min/max 289.5 525.4 spread min/max -136.4 75.3 low_thr 298.0 high_thr 401.2 low_runs [(1, 8), (13, 29)] high_runs [(53, 60), (73, 88)] longest neg (19, 23) longest pos (86, 90) DATE 2026-03-03 front min/max 320.2 597.6 settlement min/max 326.3 496.3 spread min/max -128.6 102.3 low_thr 334.0 high_thr 404.4 low_runs [(3, 3), (5, 17), (19, 29), (96, 96)] high_runs [(33, 36), (41, 48), (81, 92)] longest neg (21, 23) longest pos (10, 17) DATE 2026-03-06 front min/max -80.0 725.0 settlement min/max -80.0 714.3 spread min/max -181.7 538.8 low_thr -80.0 high_thr 567.6 low_runs [(6, 8), (11, 19), (23, 25), (39, 65)] high_runs [(69, 76), (81, 96)] longest neg (31, 34) longest pos (73, 83) DATE 2026-03-08 front min/max -80.0 670.4 settlement min/max -80.0 647.2 spread min/max -197.3 274.2 low_thr 364.2 high_thr 548.7 low_runs [(15, 17), (22, 31), (51, 62)] high_runs [(65, 72), (81, 96)] longest neg (35, 38) longest pos (42, 48) DATE 2026-03-10 front min/max -80.0 481.1 settlement min/max -80.0 451.6 spread min/max -238.8 236.0 low_thr -80.0 high_thr 348.3 low_runs [(29, 64), (66, 66)] high_runs [(1, 8), (69, 80), (89, 92)] longest neg (7...",
      "timestamp": "2026-04-09T15:06:33.315Z",
      "toolName": "tool"
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    {
      "kind": "tool_event",
      "role": "toolResult",
      "content": "Plan updated.",
      "timestamp": "2026-04-09T15:06:35.965Z",
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      "content": "[[reply_to_current]] 可以，基于当前本地样本与现有轻量特征，我建议这样筛选 2026-03-01 至 2026-03-15 的山东独立储能现货交易示范日。 ## 一、轻量候选日排序逻辑 我采用“**可讲清楚**优先，而不是单纯追求理论最大价差”的筛选逻辑，重点看 4 件事： | 维度 | 关注点 | 含义 | |---|---|---| | 价格波动 | volatility_score、极值表现 | 有波动才有示范空间，但过于混乱会降低可解释性 | | 峰谷价差 | daily_spread_mean、daily_spread_p90 | 看是否存在足够明显的“低充高放”收益带 | | 窗口可展示性 | low_charge_window_count、high_discharge_window_count、连续区间形态 | 是否能讲成“一个清晰低价充电段 + 一到两个高价放电段” | | 案例讲述性 | continuity、碎片度、规则约束适配 | 是否能在 SOC、最小持续时长、分段复杂度下讲成一个可信故事 | ### 实际排序原则 1. **先看 final_demo_score 作为基础排序** 2. **再人工校正**，把“价差很大但过碎、过极端、不利于演示”的日期往后放 3. **优先保留能讲成紧凑操作故事的日期**，即： - 低价窗口足够连续 - 高价窗口集中 - 不需要太多充放切换 - 符合 4 个结算时段以上连续动作、SOC 10%到90%、日循环不过深等简化约束 --- ## 二、Top 3 候选日期建议 ### Top 1, 2026-03-10 **综合建议：最适合做“典型示范日”** **核心依据** - 排名样本里 **final_demo_score = 37.76，rank = 1** - **daily_spread_mean = 10.23，daily_spread_p90 = 81.25** - **1 个低价充电窗口，4 个高价放电窗口**，放电展示素材最丰富 - 平均前置节点价仅 **121.41**，属于样本内很低水平，低充逻辑直观 - 区间级数据里 **29-64 时段出现超长低价/负价带**，非常适合讲“集中充电或蓄能等待” - 后段 **69-80、89-92** 附近出现较明确高价结算带，可讲“晚间择机释放” **为什么它最强** - 这一天最像“**低价塌陷, 晚间回升**”的标准储能故事 - 观众容易理解，不需要太多复杂切换 - 既有明显价差，又有很强的演示冲击力 **需要提示的 caveat** - 低价持续时间很长，容易显得“机会过大”，正式讲述时要强调 **SOC 上限、效率损失、不能无限吸收** - 高价窗口较多，实操演示建议只截取 **1 到 2 段代表性放电窗口*...",
      "timestamp": "2026-04-09T15:07:10.107Z"
    }
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}