market-daily-review

```json qsh-form { "version": 1, "task": { "placeholder": "补充复盘口径或特别要求（可选）", "required": false }, "fields": [ { "key": "date", "label": "复盘日期", "type": "date", "help": "留空时使用最近已完成的 A 股交易日" }, { "key": "focus", "label": "重点关注", "type": "text", "placeholder": "例如：北向持仓、半导体板块、龙虎榜" } ], "prompt_template": "{{#task}}任务与材料：\n{{task}}\n\n{{/task}}{{#attachments}}用户上传的材料（已放入工作区）：\n{{attachments}}\n\n{{/attachments}}执行 A 股收盘复盘。{{#date}}以 {{date}} 为目标日期。{{/date}}未指定日期时以最近已完成的 A 股交易日为目标日期。{{#focus}}重点关注 {{focus}}。{{/focus}}先核验交易日，再覆盖指数表现与估值、市场宽度、涨跌停情绪、行业与概念、龙虎榜、大宗交易、两融、北向持仓和风险提示，逐项标注数据接口与日期并说明滞后或缺失数据，输出中文报告。" } ``` # Market Daily Review Use this skill to generate factual A-share after-close review reports. Prefer Pandadata as the data source, keep every statistic traceable to an interface and data date, and never invent missing figures. ## Workflow 1. Determine the target date. If the user does not provide one, use the latest completed A-share trading day. Check `get_last_trade_date` and `get_trade_cal`; if the target date is closed, return a short "今日休市" note instead of a full report. 2. Load `pandadata-api` before making real API calls. Use its method index or search script to confirm parameters and fields; do not guess Pandadata signatures. 3. Collect data in this order: - Trading calendar and stock universe: `get_last_trade_date`, `get_trade_cal`, `get_trade_list`. - Index performance and va...