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JimLiu/baoyu-skills
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预测A股个股次日走势,输出图文并茂的 Markdown 分析报告(含详细逻辑推导、中间结果、概率量化与操作建议),面向散户与专业投资者均适用。触发条件:用户输入A股股票名称或代码(6位数字,如600519、000858),并希望获得次日走势预测;关键词包括"预测明天走势"、"明天能涨吗"、"A股分析"、"帮我分析XX股票"、"明天该买吗"、"次日预测"、"做T建议"、"短线操作"、"明日行情"、…
$ npx skills add digoal/blog --skill a-stock-predictor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install digoal/blog a-stock-predictor --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/skills_for_claude_web/a-stock-predictor .claude/skills/a-stock-predictor && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "a-stock-predictor" agent skill from https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/a-stock-predictor into .claude/skills/a-stock-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "a-stock-predictor", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/a-stock-predictorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add digoal/blog --skill a-stock-predictor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install digoal/blog a-stock-predictor --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/skills_for_claude_web/a-stock-predictor .agents/skills/a-stock-predictor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "a-stock-predictor" agent skill from https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/a-stock-predictor into .agents/skills/a-stock-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "a-stock-predictor", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add digoal/blog --skill a-stock-predictor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install digoal/blog a-stock-predictor --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/skills_for_claude_web/a-stock-predictor .cursor/skills/a-stock-predictor && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "a-stock-predictor" agent skill from https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/a-stock-predictor into .cursor/skills/a-stock-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "a-stock-predictor", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/digoal/blog.git --path skills/skills_for_claude_web/a-stock-predictor--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add digoal/blog --skill a-stock-predictor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install digoal/blog a-stock-predictor --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/skills_for_claude_web/a-stock-predictor .gemini/skills/a-stock-predictor && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "a-stock-predictor" agent skill from https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/a-stock-predictor into .gemini/skills/a-stock-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "a-stock-predictor", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install digoal/blog a-stock-predictorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add digoal/blog --skill a-stock-predictor -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/skills_for_claude_web/a-stock-predictor .github/skills/a-stock-predictor && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "a-stock-predictor" agent skill from https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/a-stock-predictor into .github/skills/a-stock-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "a-stock-predictor", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add digoal/blog --skill a-stock-predictor -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install digoal/blog a-stock-predictor --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/skills_for_claude_web/a-stock-predictor .opencode/skills/a-stock-predictor && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "a-stock-predictor" agent skill from https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/a-stock-predictor into .opencode/skills/a-stock-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "a-stock-predictor", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
a-stock-predictor预测A股个股次日走势,输出图文并茂的 Markdown 分析报告(含详细逻辑推导、中间结果、概率量化与操作建议),面向散户与专业投资者均适用。触发条件:用户输入A股股票名称或代码(6位数字,如600519、000858),并希望获得次日走势预测;关键词包括"预测明天走势"、"明天能涨吗"、"A股分析"、"帮我分析XX股票"、"明天该买吗"、"次日预测"、"做T建议"、"短线操作"、"明日行情"、…
A Stock Predictor is an agent skill from digoal/blog. 预测A股个股次日走势,输出图文并茂的 Markdown 分析报告(含详细逻辑推导、中间结果、概率量化与操作建议),面向散户与专业投资者均适用。触发条件:用户输入A股股票名称或代码(6位数字,如600519、000858),并希望获得次日走势预测;关键词包括"预测明天走势"、"明天能涨吗"、"A股分析"、"帮我分析XX股票"、"明天该买吗"、"次日预测"、"做T建议"、"短线操作"、"明日行情"、"值得持有吗"、"止盈止损怎么设"等。即使用户只说"帮我看看贵州茅台明天怎么走"或"600519明天能不能买",也应使用本 skill。输出 Markdown 文件保存到当前项目 markdown/ 目录,要求逻辑清晰、概率可量化、图文并茂,投资小白也能看懂。
Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Documents & Office, covering Markdown. The repository describes itself as: AI,Opensource,Database,Business,Finance,Minds. git clone --depth 1 https://github.com/digoal/blog. The licence is GPL-2.0.
11 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit ad6fcb7. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and mermaid).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
A Stock Predictor loads about 2.6k tokens when it runs. Until then it costs about 87 tokens; SKILL.md has 270 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from digoal/blog at commit ad6fcb7, republished under its GPL-2.0 licence (© digoal). 270 words, ~2,609 tokens.
.claude/skills/a-stock-predictor/SKILL.md (or your agent's skills folder).A股市场有其独特性,不同于美股的七大特征:
因此,使用专为A股设计的 PACE框架:
| 字母 | 维度名称 | 含义 | 权重 |
|---|---|---|---|
| P | Policy & Macro 政策宏观 | 政策消息、宏观数据、监管动向 | 20% |
| A | Auction & Flow 资金拍卖 | 主力资金、北向资金、龙虎榜、融资融券 | 25% |
| C | Chart & Technicals 图表技术 | 技术形态、均线、MACD、KDJ、量价关系 | 25% |
| E | Emotion & Sentiment 情绪舆论 | 板块热度、游资动向、消息面、市场情绪 | 20% |
| + | Catalyst & Event 催化事件 | 财报、重大公告、分析师评级、行业事件 | 10% |
七个子维度补充(嵌套在PACE中):
搜索要点:
评分逻辑(满分20分):
政策利好(+10至+20)
政策中性(+10)
政策利空(+0至+10)
外围顺风(额外+0至+3加权)
外围逆风(额外-0至-3加权)A股资金分析是最重要的核心维度,分四个子层:
2.1 北向资金(满分8分)
北向单日净买>10亿 → 强烈利多(8分)
北向单日净买>5亿 → 温和利多(6分)
北向中性 → 中性(4分)
北向单日净卖>5亿 → 温和利空(2分)
北向单日净卖>10亿 → 强烈利空(0分)2.2 主力资金净流向(满分8分)
主力净流入率 > +5% → 积极(8分)
主力净流入率 0~5% → 中性偏多(6分)
主力净流入率 -5~0% → 中性偏空(4分)
主力净流入率 < -5% → 出逃(0分)2.3 龙虎榜数据(满分5分) (仅当日换手率>3倍历史均值或股价涨跌幅>7%时触发)
2.4 融资融券(满分4分)
3.1 均线系统(满分8分)
A股最重要的均线:MA5、MA10、MA20(短线)、MA60(中线)、MA250(年线)
判断逻辑:
①价格位置:站上/跌破MA20 → ±3分
②均线多头排列(MA5>MA10>MA20)→ +2分
③均线死叉/金叉形成 → ±2分
④放量突破/跌破均线 → 额外±1分3.2 量价关系(满分7分)— A股最核心的量化信号
价涨量增(放量上涨)→ 确认趋势 +7分
价涨量缩(缩量上涨)→ 追高风险 +3分
价跌量缩(缩量下跌)→ 洗盘信号 +5分
价跌量增(放量下跌)→ 主力出货 +0分
关键:量比(当日量/过去5日均量)
量比>2且价涨 → 人气旺盛
量比<0.5且价跌 → 缩量整理3.3 MACD+KDJ组合(满分6分)
MACD:
- 红柱扩大 +2,绿柱缩小 +1(A股MACD金叉相对滞后但可靠)
- DIF上穿DEA(金叉)+2,下穿(死叉)-2
- 二次金叉(背离修复)→ 特别强烈信号 +3
KDJ:
- K>D且均线向上 +2
- KDJ<20(超卖区金叉)→ 反弹信号 +2
- KDJ>80(超买)→ 注意风险 +03.4 涨跌停与关键位(满分4分)
当日涨停(封板坚实 封单>5000万)→ 次日高开概率大(+4分)
当日涨停(开板次数多,封板弱)→ 次日高开低走风险(+1分)
当日跌停(恐慌性)→ 次日继续跌或反包(判断需结合消息面)
接近前高阻力位(<2%)→ 突破概率评估4.1 板块热度与轮动(满分8分)
A股板块轮动极为明显,个股往往跟板块走:
所在板块当日领涨(前5)+ 明日有延续性 → +8分
所在板块当日跟涨(前20) → +5分
所在板块当日中性 → +3分
所在板块当日领跌 → +0分判断板块延续性:看板块龙头的封板情况、板块内涨停数量
4.2 市场整体情绪(满分6分)
两市涨停家数 > 100 → 情绪亢奋(+6分)
两市涨停家数 50~100 → 情绪良好(+4分)
两市涨停家数 20~50 → 情绪中性(+2分)
两市涨停家数 < 20 → 情绪低迷(+0分)
涨跌比(涨家数/跌家数)> 2 → 额外+1分4.3 消息面情绪(满分6分)
利好:公司层面正向公告/媒体正面报道 +4~6
中性:无重大消息 +3
利空:负面公告/质疑报道 +0~1重大利好催化(定向增发、股份回购、重大合同、业绩超预期)→ +8~10分
无催化事件 → +5分(基准)
财报即将(3日内),历史经常超预期 → +7分
财报即将,历史经常不及预期 → +2分
重大负面催化(问询函、立案调查、业绩预告亏损) → +0分搜索1:"{股票名称/代码} 今日行情 涨跌 成交量"
搜索2:"{股票名称} 主力资金 北向资金 净流入"
搜索3:"{股票名称} 龙虎榜 机构席位 {当前日期}"
搜索4:"{股票名称} MACD KDJ 技术分析 均线"
搜索5:"{股票板块} 板块行情 今日热点 涨停股"
搜索6:"{股票名称} 最新公告 研报 消息 {当前月份}"
搜索7:"A股 今日市场情绪 涨停家数 两市行情"
搜索8:"A股 北向资金 今日 净买入净卖出"
搜索9(可选):"{股票名称} 融资融券 余额变化"
搜索10(可选):"{股票名称} 业绩预告 财报日期"数据收集清单(必须尽量填满):
| 维度 | 关键数据项 |
|---|---|
| P-政策 | 隔夜外围收盘、当日政策消息、指数方向 |
| A-资金 | 北向净流入、主力净流入率、龙虎榜(如有)、融资余额变化 |
| C-技术 | 收盘价、涨跌幅、MA5/MA20位置、量比、MACD状态、KDJ值 |
| E-情绪 | 两市涨停数、板块排名、相关消息面 |
| +-催化 | 近期公告、财报日期、分析师评级 |
对每个维度独立评分,必须写出每个分数的理由,不能直接给结论分。
P得分(0-20):[具体政策/外围情况 → 理由 → 分数]
A得分(0-25):[北向X分 + 主力X分 + 龙虎X分 + 融资X分 → 合计]
C得分(0-25):[均线X分 + 量价X分 + MACD/KDJ X分 + 关键位X分 → 合计]
E得分(0-20):[板块X分 + 市场情绪X分 + 消息X分 → 合计]
+得分(0-10):[催化事件描述 → 分数]
总分 = P + A + C + E + (+) (满分100)总分 → 基准看涨概率转换表:
| 总分区间 | 基准看涨概率 | 解读 |
|---|---|---|
| 80-100 | 65-75% | 强烈看多信号 |
| 65-80 | 55-65% | 温和看多信号 |
| 50-65 | 45-55% | 中性/震荡预期 |
| 35-50 | 35-45% | 温和看空信号 |
| 0-35 | 25-35% | 强烈看空信号 |
三情景概率分布(必须合计100%):
预期收益率计算:
E(r) = P_A × 典型涨幅 + P_B × 0.5% + P_C × 典型跌幅
若 E(r) > 0.5% 且 P_A/P_C > 1.5(盈亏比),具有操作价值
若 E(r) < 0 或 P_C > 40%,建议回避或轻仓基于技术分析,输出以下具体数字(非模糊描述):
建议买入区间:[价格下限, 价格上限](基于支撑位)
第一目标位:[价格](基于压力位/涨幅预期)
第二目标位:[价格](如动能足够)
技术止损位:[价格](跌破关键支撑则止损)
最大允许亏损:不超过 -3%(硬性规定)
建议仓位:[轻仓10-20% / 标准30-40% / 重仓50%以上](基于置信度)# {股票名称}({代码})次日走势预测报告
> 预测日期:{今日} → 预测交易日:{明日}
> 分析框架:PACE七维量化模型 | 请结合自身风险承受能力决策
---
## ⚡ 核心结论(30秒速览)
> **[🟢强烈看多 / 🟡温和看多 / ⚪震荡观望 / 🟠温和看空 / 🔴强烈看空]**
>
> **建议操作:** [买入/减仓/观望/回避]
> **核心逻辑:** [一句话]
> **置信度:** [高 / 中 / 低]
---
## 📊 PACE七维评分仪表盘
[SVG雷达图 + ASCII评分汇总]
---
## 🏛️ 第一维:政策宏观(P,满分20)
[外围市场 → 政策消息 → 指数趋势 → P得分及理由]
---
## 💰 第二维:资金拍卖(A,满分25)
### 北向资金
### 主力净流向
### 龙虎榜(如触发)
### 融资融券
[各子维度分析 + A总得分]
---
## 📈 第三维:图表技术(C,满分25)
### 均线系统
### 量价关系
### MACD + KDJ
### 关键价格位
[ASCII走势示意图 + C总得分]
---
## 🌡️ 第四维:情绪舆论(E,满分20)
### 板块热度与轮动
### 两市整体情绪
### 消息面
[E总得分]
---
## 🔮 第五维:催化事件(+,满分10)
[近期公告/研报/财报日/行业事件 → +得分]
---
## 🎯 综合评分与概率分布
[总分 = P+A+C+E+ → 情景概率 → 预期收益率]
---
## 💡 风控参数与操作建议
[买入区间 / 目标位 / 止损位 / 仓位建议]
---
## ⚠️ 风险提示
[免责声明 + 置信度说明 + 特殊风险]用SVG绘制五边形雷达图,显示五维评分:
┌──────────────────────────────────────────────────┐
│ {股票名称} 近期走势示意(非精确K线) │
│ │
│ 价 ↑ 阻力位 {价格} ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ 格 │ ╭──╮ │
│ │ ╭╯ ╰──╮ 当前价 {价格} ← │
│ │ ╭╯ ╰───── │
│ │ ─────────────── MA20({价格}) ───── │
│ │ ─ ─ ─ ─ ─ ─ ─ MA5({价格}) ─ ─ ─ │
│ │ ════════════════ MA60({价格}) ═════ │
│ │ 支撑位 {价格} ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ └──────────────────────────────── 时间 → │
└──────────────────────────────────────────────────┘ ┌─────────────────────────────────────────────────┐
│ 次日三情景概率分布 │
├─────────────────────────────────────────────────┤
│ 🟢 看涨(>+2%) ████████████░░░░░░░░ XX% │
│ ⚪ 震荡(-2%~+2%) ████████░░░░░░░░░░ XX% │
│ 🔴 看跌(<-2%) ████░░░░░░░░░░░░░░░░ XX% │
├─────────────────────────────────────────────────┤
│ 预期收益率:E(r) = XX% │
│ 盈亏比(看涨/看跌)= X.X : 1 │
└─────────────────────────────────────────────────┘ ┌──────────────┬──────┬────────┬──────────────────┐
│ 信号指标 │ 方向 │ 强度 │ 当前值 │
├──────────────┼──────┼────────┼──────────────────┤
│ 北向资金 │ ↑ │ ★★★☆ │ +XX亿(净买入) │
│ 主力净流入 │ ↑ │ ★★☆☆ │ +X.X% │
│ MA20位置 │ ↑ │ ★★★☆ │ 站上/已突破 │
│ 量比 │ → │ ★★☆☆ │ X.X倍 │
│ MACD │ ↑ │ ★★☆☆ │ 金叉/红柱扩张 │
│ KDJ │ ↓ │ ★★★☆ │ 超买区 XX │
│ 板块热度 │ ↑ │ ★★★★ │ 板块今日领涨 │
│ 市场情绪 │ → │ ★★☆☆ │ 涨停XX家 │
└──────────────┴──────┴────────┴──────────────────┘
综合信号:X多 X空 X中性flowchart TD
A[输入股票] --> B[PACE数据采集]
B --> C{数据完整性检查}
C -->|完整| D[五维独立评分]
C -->|不完整| E[标注缺失 降低置信度]
E --> D
D --> F{总分计算}
F -->|80-100| G[🟢 强烈看多]
F -->|65-80| H[🟡 温和看多]
F -->|50-65| I[⚪ 中性震荡]
F -->|35-50| J[🟠 温和看空]
F -->|0-35| K[🔴 强烈看空]
G & H & I & J & K --> L[三情景概率分布]
L --> M[风控参数计算]
M --> N[输出Markdown报告]| 术语 | 通俗解释 |
|---|---|
| T+1 | 今天买的股票,明天才能卖。所以预测明天行情更重要 |
| 涨停板 | A股规定单日最多涨10%(ST股5%),封住涨停意味着买不进去 |
| 北向资金 | 通过沪深港通从香港流入A股的境外资金,俗称"聪明钱" |
| 主力资金 | 超大单买入卖出,通常是机构或大户,比散户更有信息优势 |
| 龙虎榜 | 当天涨跌幅超7%或换手率超3倍时,交易所公示的前5买家和卖家名单 |
| 量比 | 今天成交量 ÷ 过去5天平均成交量。>2说明量能放大,行情活跃 |
| MA5/MA20 | 过去5天/20天的平均股价。价格在均线上方=趋势健康 |
| MACD | 两条均线的差值。金叉(短线穿越长线向上)是看涨信号 |
| KDJ | 超买超卖指标。>80可能超买要小心,<20可能超卖有反弹机会 |
| 融资余额 | 散户借钱炒股的总量。增加说明看多情绪升温 |
| 封单 | 挂在涨停板上等着卖的买单数量。越大封板越稳固 |
| 板块轮动 | A股常见规律:今天涨科技,明天换医药,热点在板块间流动 |
| 盈亏比 | 预期盈利/预期亏损。>1.5才值得出手,小于1不划算 |
| 置信度 | 这份分析有多可靠。数据越完整、信号越一致,置信度越高 |
→ 特别分析封板强度(封单占流通盘比例)
→ 评估次日高开概率(强势涨停 vs 尾盘涨停)
→ 强封(封单>3亿且全天未打开)→ 次日高开概率70%以上
→ 弱封(多次打开后封板)→ 次日高开低走风险大
→ 操作建议:若已持有,高开后注意观察分时量能决定是否出→ 区分原因:基本面利空 vs 大盘拖累 vs 游资出货
→ 基本面利空跌停 → 次日大概率继续,建议回避
→ 恐慌性跌停(无重大利空) → 存在次日反包机会
→ 需查龙虎榜:机构大量买入跌停 → 强烈反转信号→ 涨跌幅限制±5%,预测逻辑不同
→ 基本面风险极高,不建议短线操作
→ 报告中明确标注警告→ 标注哪些数据缺失
→ 置信度降至"低"
→ 建议等待完整数据后再决策
→ 该维度取中间分(该维度满分×0.5)## ⚠️ 风险提示与免责声明
### 硬性止损规则(必须遵守)
- **技术止损**:跌破 [关键支撑位] 无条件止损
- **幅度止损**:亏损超过 -3% 无条件离场(T+1限制下,次日开盘必须卖)
- **时间止损**:买入后持续3日未达预期,考虑离场
### 特别风险警告
- ⚠️ 若股票距离财报发布 ≤ 5个交易日:仓位减半或回避
- ⚠️ 若大盘VIX性质指标(恐慌指数)异常:降低仓位
- ⚠️ 若当日重大政策出台(未消化完):谨慎对待次日预测
- ⚠️ 本报告基于公开信息和量化模型,不构成投资建议
### 置信度说明
- 🟢 高置信度:数据完整,信号一致性>70%
- 🟡 中置信度:数据基本完整,信号存在分歧
- 🔴 低置信度:关键数据缺失,信号严重矛盾
### 模型局限性
本模型次日预测准确率行业基准约55-62%,
重大突发事件(黑天鹅)将使预测失效。
**投资有风险,入市需谨慎。本报告仅供学习参考。**文件名:{股票代码}-{股票名称}-{YYYYMMDD}.md
保存路径:markdown/
编码:UTF-8
语言:中文为主,专业术语保留并附注解
图表:至少包含雷达图、走势示意图、概率分布图、信号汇总表用户输入: "帮我分析一下贵州茅台(600519)明天的走势"
执行流程:
© digoal, GPL-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/skills_for_claude_web/a-stock-predictor of digoal/blog.
Open the folder on GitHubat commit ad6fcb7
A Stock Predictor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| A Stock Predictor this skilldigoal/blog | 8.6k | — | ~2.6k | Automated safety check: Pass | GPL-2.0 | |
| Markdown Article FormatterJimLiu/baoyu-skills | 27k | 6 repos | ~3.5k | Automated safety check: Pass | MIT | |
| MarkitdownImCa0/just-laws | 781 | 14 repos | ~3.2k | Automated safety check: Notes | MIT | |
| Obsidian MarkdownAtmosphere/atmosphere | 3.8k | 20 repos | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Crosspostingwasp-lang/wasp | 19k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Gzh Designisjiamu/gzh-design-skill | 4k | — | ~2.2k | Automated safety check: Pass | AGPL-3.0 |
JimLiu/baoyu-skills
Reformats plain text or Markdown articles with frontmatter, a title, a summary, headings, bold, lists and code blocks, and saves a separate formatted copy.
ImCa0/just-laws
Convert files and office documents to Markdown. An agent skill from ImCa0/just-laws.
Atmosphere/atmosphere
Create and edit Obsidian Flavored Markdown with wikilinks, embeds, callouts, properties, and other Obsidian-specific syntax.
wasp-lang/wasp
Crosspost Wasp blog articles (MDX) to DEV.to and Medium. An agent skill from wasp-lang/wasp.
isjiamu/gzh-design-skill
微信公众号文章排版引擎,将 Markdown 转换为可直接粘贴到公众号编辑器的 HTML。主题风格从 references/theme-index.md 注册的自定义主题库中选取,自动章节编号、关键词下划线标记、引言卡片、目录导航、代码块、图片/GIF、作者签名。支持 Markdown / Word(.docx) / PDF / 纯文本输入(非 Markdown…
supabase/supabase
Review Supabase docs changes locally in your supabase/supabase checkout — either an open PR (triage, classify, verify) or your own branch before opening a PR (local self-review).
digoal/blog
三层审查模型,逐段逐句验证文章真伪、证据链与逻辑结构。Use when the user asks to fact-check, verify, audit, or evaluate the credibility of an article, essay, report, opinion piece, social-media post, or any written claim —…
digoal/blog
Find latent bugs in a local PostgreSQL source tree (RELxxSTABLE branch or HEAD) the way a core hacker does: build a heavily-poisoned debug instance (cassert + cache-discard + -O0/-ggdb3 + core…
digoal/blog
Portable digital employee distilled from digoal's personal blog for PostgreSQL, PolarDB, DuckDB, AI+database, vector/RAG, database operations, source-code reading, technical content creation…
digoal/blog
从论文 PDF 文件或论文 PDF URL 生成通俗易懂、图文并茂、带批判性评估的中文 Markdown 解读,并保存到当前项目的 markdown 目录。Use when the user asks to interpret,精读,解读,summarize,explain,analyze, or write an article from an academic paper PDF…
digoal/blog
Analyze a product from documentation, websites, PDFs, articles, release notes, pricing pages, app listings, reviews, filings, or related links; save separate intermediate analyses from seven roles…
digoal/blog
Turn a blog post, article, notes, or any source material into a set of vertical poster images — one cover plus several coherent content slides that explain the core points.
Categories
预测A股个股次日走势,输出图文并茂的 Markdown 分析报告(含详细逻辑推导、中间结果、概率量化与操作建议),面向散户与专业投资者均适用。触发条件:用户输入A股股票名称或代码(6位数字,如600519、000858),并希望获得次日走势预测;关键词包括"预测明天走势"、"明天能涨吗"、"A股分析"、"帮我分析XX股票"、"明天该买吗"、"次日预测"、"做T建议"、"短线操作"、"明日行情"、…. A Stock Predictor is an agent skill from digoal/blog.
A Stock Predictor fits situations like: tasks that involve Markdown.
Run `npx skills add digoal/blog --skill a-stock-predictor -a claude-code`. Or copy the skill folder (skills/skills_for_claude_web/a-stock-predictor in digoal/blog) into .claude/skills/a-stock-predictor in your project. Claude Code loads it when a task matches its description.
Run `npx skills add digoal/blog --skill a-stock-predictor -a codex`. Or copy the skill folder (skills/skills_for_claude_web/a-stock-predictor in digoal/blog) into .agents/skills/a-stock-predictor in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add digoal/blog --skill a-stock-predictor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/a-stock-predictor, .gemini/skills/a-stock-predictor, .github/skills/a-stock-predictor and .opencode/skills/a-stock-predictor in your project.
SKILL.md names no scripts, command-line tools or credentials: A Stock Predictor is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
A Stock Predictor is published under the GPL-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with A Stock Predictor: Markdown Article Formatter (JimLiu/baoyu-skills, 27k stars), Markitdown (ImCa0/just-laws, 781 stars), Obsidian Markdown (Atmosphere/atmosphere, 3.8k stars) and Crossposting (wasp-lang/wasp, 19k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
digoal (a GitHub user) maintains it in digoal/blog, which has 8,588 GitHub stars. The repository holds 98 skills in this directory. The repository was last updated on October 9, 2026.
Source: digoal/blog on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.