Stock API
zhangxiangliang/stock-api
Fetch real-time stock quotes, K-line (candlestick) history, and search symbols for China A-shares, Hong Kong, and US markets.
缠论+基本面+财报+估值综合股票分析技能，生成专业投研报告（含 PDF）. An agent skill from LeoYeAI/openclaw-master-skills.
Install Chan Stock Analysis
$ npx skills add LeoYeAI/openclaw-master-skills --skill chan-stock-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills chan-stock-analysis --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/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/chanlun-stock-analysis .claude/skills/chan-stock-analysis && 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 "chan-stock-analysis" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/chanlun-stock-analysis into .claude/skills/chan-stock-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chan-stock-analysis", 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/LeoYeAI/openclaw-master-skills/tree/main/skills/chanlun-stock-analysisType 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 LeoYeAI/openclaw-master-skills --skill chan-stock-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills chan-stock-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/chanlun-stock-analysis .agents/skills/chan-stock-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "chan-stock-analysis" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/chanlun-stock-analysis into .agents/skills/chan-stock-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chan-stock-analysis", 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 LeoYeAI/openclaw-master-skills --skill chan-stock-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills chan-stock-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/chanlun-stock-analysis .cursor/skills/chan-stock-analysis && 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 "chan-stock-analysis" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/chanlun-stock-analysis into .cursor/skills/chan-stock-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chan-stock-analysis", 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/LeoYeAI/openclaw-master-skills.git --path skills/chanlun-stock-analysis--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 LeoYeAI/openclaw-master-skills --skill chan-stock-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills chan-stock-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/chanlun-stock-analysis .gemini/skills/chan-stock-analysis && 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 "chan-stock-analysis" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/chanlun-stock-analysis into .gemini/skills/chan-stock-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chan-stock-analysis", 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 LeoYeAI/openclaw-master-skills chan-stock-analysisInstalls 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 LeoYeAI/openclaw-master-skills --skill chan-stock-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/chanlun-stock-analysis .github/skills/chan-stock-analysis && 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 "chan-stock-analysis" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/chanlun-stock-analysis into .github/skills/chan-stock-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chan-stock-analysis", 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 LeoYeAI/openclaw-master-skills --skill chan-stock-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills chan-stock-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/chanlun-stock-analysis .opencode/skills/chan-stock-analysis && 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 "chan-stock-analysis" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/chanlun-stock-analysis into .opencode/skills/chan-stock-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chan-stock-analysis", 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.
Facts
- Skill name
chan-stock-analysis- GitHub stars
- 2.2k
- Token cost
- ~2.4k tokens
- SKILL.md length
- 397 words
- Files
- 8 (incl. references, assets)
- Skills in repo
- 1,235
- Repo updated
- First seen
- Licence
- MIT
At a glance
缠论+基本面+财报+估值综合股票分析技能，生成专业投研报告（含 PDF）. An agent skill from LeoYeAI/openclaw-master-skills.
- Works in 3 steps: 识别包含关系并合并K线 → 标注顶分型（▼）和底分型（▲） → 连接笔：描述近期主要笔的方向和幅度
- : 用户提供股票代码，要求进行深度股票分析、缠论技术分析、基本面研究、财报解读、估值分析、综合投研报告
- SKILL.md covers 使用场景, 快速开始, 详细用法 and 配置选项, plus 4 more sections
- Calls pip; needs TUSHARE_TOKEN
What it does
Chan Stock Analysis is an agent skill from LeoYeAI/openclaw-master-skills. 缠论+基本面+财报+估值综合股票分析技能，生成专业投研报告（含 PDF）。 Use when: 用户提供股票代码，要求进行深度股票分析、缠论技术分析、基本面研究、财报解读、估值分析、综合投研报告。 NOT for: 实时行情播报、简单股价查询、非股票类金融分析。 触发词：缠论分析、股票分析报告、技术面+基本面、综合研究、投研报告、深度分析、估值分析、财报分析、买卖点分析
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files and assets (for example `CHANGELOG.md`, `README.md` and `_meta.json`).
It sits in Business, Finance & HR, covering Stock and market analysis. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.
When your agent uses it
- : 用户提供股票代码，要求进行深度股票分析、缠论技术分析、基本面研究、财报解读、估值分析、综合投研报告
- Tasks that involve Stock and market analysis
Example prompts
- “/chan-stock-analysis”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- 识别包含关系并合并K线
- 标注顶分型（▼）和底分型（▲）
- 连接笔：描述近期主要笔的方向和幅度
What it can do on your machine
Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.
Tool permissions
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.
Runs code
Shell commands in SKILL.md call:
pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
TUSHARE_TOKEN
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Chan Stock Analysis loads about 2.4k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 52 tokens; SKILL.md has 397 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.
Safety
Auto-check passed
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.
SKILL.md
The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 397 words, ~2,419 tokens.
Download SKILL.mdSave it as
.claude/skills/chan-stock-analysis/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.- name
- chan-stock-analysis
- description
- 缠论+基本面+财报+估值综合股票分析技能，生成专业投研报告（含 PDF）。 Use when: 用户提供股票代码，要求进行深度股票分析、缠论技术分析、基本面研究、财报解读、估值分析、综合投研报告。 NOT for: 实时行情播报、简单股价查询、非股票类金融分析。 触发词：缠论分析、股票分析报告、技术面+基本面、综合研究、投研报告、深度分析、估值分析、财报分析、买卖点分析
📈 缠论+基本面+估值 综合股票分析技能
输入股票代码，输出一份涵盖缠论技术面、基本面、估值面的专业投研报告，并自动生成排版精美的 PDF 文件。
使用场景
✅ Use when（适用）
- 用户提供股票代码（如
600519、贵州茅台、AAPL），要求进行综合分析 - 要求生成完整投研报告、买卖点判断、目标价预测
- 需要缠论结构分析（中枢、笔、背驰、买卖点）
- 要求基本面财报解读、估值对比
- 触发词：缠论分析、股票分析报告、投研报告、技术面+基本面、深度分析、估值分析、买卖点分析、财报解读
❌ NOT for（不适用）
- 实时股价查询（只看价格，不做分析）
- 简单涨跌预测（无深度分析需求）
- 非 A 股/港股/美股标的
- 基金、债券、期货等非股票品种
快速开始
用户：分析一下 600519
↓
技能自动执行：
1. 解析股票代码 → 贵州茅台 600519.SH
2. 实时获取行情、财务、资金数据
3. 缠论结构 + 多指标共振技术分析
4. 基本面盈利/成长/健康度分析
5. PE/PB/DCF 多维估值
6. 输出 Markdown 投研报告
7. 自动生成专业排版 PDF详细用法
分析流程（严格按阶段执行）
🔴 阶段0：解析股票代码
接收用户输入的股票代码，自动处理格式：
- 输入
600519或贵州茅台→ 转换为600519.SH - 输入
000001或平安银行→ 转换为000001.SZ - 输入
300750→ 转换为300750.SZ（创业板） - 输入
688xxx→ 转换为688xxx.SH（科创板） - 支持港股（
.HK）和美股（.US）
调用 stock_basic 接口确认公司名称、行业、上市交易所。
🔴 阶段1：实时数据采集
并行获取以下数据（全部通过 finance-data-retrieval skill 调用）：
1.1 行情数据
调用: daily(ts_code=XX, start_date=近250个交易日) → 日线OHLCV
调用: weekly(ts_code=XX, start_date=近104周) → 周线数据
调用: daily_basic(ts_code=XX, trade_date=最新) → PE(TTM)、PB、市值、换手率、量比1.2 技术指标数据（优先用接口，次选自行计算）
调用: stk_factor(ts_code=XX, start_date=近250日) → 预计算技术指标（若接口支持）
包含：MA5/MA10/MA20/MA60、MACD系列、RSI、KDJ、BOLL、ATR、OBV
若 stk_factor 不可用，则基于 daily 数据自行计算：
- 均线：MA5 / MA10 / MA20 / MA60 / MA120 / MA250
- 动量：MACD(12,26,9) → DIF、DEA、柱
- 振荡：RSI(6/12/24)、KDJ(9,3,3)、CCI(14)、WR(14)
- 波动率：BOLL(20,2)、ATR(14)
- 量价：OBV、BIAS(20)、BIAS(60)
- 趋势强度：ADX/DMI(14)1.3 资金流向数据
调用: moneyflow(ts_code=XX, start_date=近20个交易日) → 主力大单净流入
调用: moneyflow_hsgt(start_date=近10日) → 北向资金（如为沪深300成分股）1.4 财务数据（确定最新可获取报告期）
根据当前日期动态判断：
- A股年报披露截止4月30日；三季报截止10月31日；中报截止8月31日；一季报截止4月30日
- 优先使用已披露的最新期次
调用: income(ts_code=XX, period=最新报告期) → 利润表
调用: balancesheet(ts_code=XX, period=最新报告期) → 资产负债表
调用: cashflow(ts_code=XX, period=最新报告期) → 现金流量表
调用: fina_indicator(ts_code=XX, period=最新报告期) → 财务指标（ROE等）
获取近4个报告期数据用于趋势分析1.5 最新公告与新闻
WebSearch: "{公司名} 最新公告 {当前年月}"
WebSearch: "{公司名} 业绩预告 年报"
WebSearch: "{公司名} 股票 最新消息"🔴 阶段2：技术分析（缠论主体 + 多指标共振）
参考文件：references/chan-theory.md
2.1 缠论结构分析（主框架）
K线处理与分型识别（基于日线250根 + 周线104根）：
- 识别包含关系并合并K线
- 标注顶分型（▼）和底分型（▲）
- 连接笔：描述近期主要笔的方向和幅度
中枢识别（日线级别）：
- 识别近期3~5个主要中枢，标注区间 [ZD, ZG]
- 分析中枢序列方向，判断大趋势（上涨/下跌/震荡）
- 标注当前价格相对中枢的位置（中枢内/突破中枢上方/跌破中枢下方）
周线级别验证：
- 用周线判断更大级别趋势方向
- 确认日线操作方向与周线趋势一致
2.2 MACD背驰分析（缠论核心辅助）
基于MACD（12,26,9）——日线+周线双周期：
- 识别近期是否存在趋势背驰（红柱/绿柱面积收缩）
- 判断背驰级别（日线背驰 vs 周线背驰，级别越高越重要）
- 标注背驰信号的可信度（强/中/弱）
2.3 趋势追踪指标组（A类）
均线系统（MA5/10/20/60/120/250）：
- 判断多头/空头/均线粘合排列
- 金叉/死叉信号及关键均线的支撑压力
- 年线（MA250）：牛熊分界参考
- 半年线（MA120）：中长期趋势判断
一目均衡表（Ichimoku）：
- 判断价格是否在云层上方（多头）/下方（空头）
- 转换线与基准线的TK交叉信号
- 云层厚薄判断支撑压力强度
ADX/DMI：
- ADX数值：判断当前是趋势市（>25）还是震荡市（<20）
- +DI/-DI方向：当前多空力量对比
- 重要：ADX<20时缠论震荡策略，ADX>25时缠论趋势策略
2.4 动量振荡指标组（B类）—— 超买超卖共振
RSI（6/12/24三周期）：
- 三周期共振超买（均>70）或超卖（均<30）信号强度更高
- 重点关注RSI顶背离/底背离（价格新高低而RSI未跟）
- RSI50分水岭：站上看多，跌破看空
KDJ（9,3,3）：
- 高位（>80）死叉卖出，低位（<20）金叉买入
- J值极端值（>100或<0）作为超买超卖的敏感预警
- KDJ底背离与缠论买点共振：信号强度+2
CCI（14日）：
- 从极度超买区（>200）回落过+100：卖出确认
- 从极度超卖区（<-200）回升过-100：买入确认
- 与RSI/KDJ形成三重超卖共振时，买入信号极强
WR威廉指标（14日）：
- 进入超卖区（<-80）并开始回升：配合KDJ确认底部
2.5 波动率指标组（C类）—— 空间与风险
布林带（BOLL，MA20±2σ）：
- 布林带宽度变化：收口→突破方向，开口→趋势延续
- 价格触及下轨+底分型：强力买入共振
- 价格触及上轨+顶分型：强力卖出共振
- 价格突破上轨"走轨"：强势追多机会
ATR（14日）：
- 计算动态止损位：止损 = 买入价 - 2×ATR
- 计算目标位：目标 = 买入价 + 3×ATR（风险收益比1:1.5）
- ATR扩张信号：波动率提升，趋势启动确认
乖离率（BIAS20/BIAS60）：
- BIAS20 > +10%：短期超买预警
- BIAS20 < -10%：短期超卖，关注买入
- BIAS60 < -20%：中期严重低估，可关注长线布局
2.6 量价关系指标组（D类）—— 量是价的先行
OBV能量潮：
- OBV持续上升/下降：资金流向趋势确认
- OBV背离（价格新高而OBV未新高）：趋势弱化预警
量比 + 换手率：
- 底部区域量比突然放大（>2.5）：主力吸筹信号
- 高位持续高换手（>10%）：出货嫌疑
- 缩量下跌（量比<0.5）：抛压减弱，底部可能临近
VWAP：
- 价格回踩VWAP获支撑：机构成本线，买入共振
- 价格跌破VWAP且无法收复：弱势信号
MFI资金流量指标：
- MFI<20超卖 + RSI<30：双重超卖共振，强烈买入信号
2.7 资金面分析（E类）
主力大单净流入（moneyflow接口）：
- 近5日主力净流入/流出趋势
- 连续净流入>3日：主力在建仓
- 价格上涨+大单净流出：主力出货，警惕
北向资金（沪深300成分股适用）：
- 连续净买入：外资认可
- 大幅净流出：外资撤离压力
2.8 多指标共振评分（买入方向）
按照 references/chan-theory.md 第四节"多指标共振评分系统"，对以下14个维度逐一打分：
| 类别 | 检查项 | 结论 | 得分 |
|---|---|---|---|
| 缠论结构 | 日线买卖点位置 | ? | 0~3 |
| 缠论结构 | MACD背驰 | ? | 0~2 |
| 趋势指标 | 均线多头/空头排列 | ? | 0~1 |
| 趋势指标 | 一目云位置 | ? | 0~1 |
| 动量指标 | RSI底背离/超卖 | ? | 0~2 |
| 动量指标 | KDJ低位金叉 | ? | 0~2 |
| 动量指标 | CCI从-200回升 | ? | 0~1 |
| 波动率 | 布林下轨+底分型 | ? | 0~2 |
| 波动率 | ATR动态止损合理 | ? | 0~1 |
| 量价 | OBV底背离 | ? | 0~2 |
| 量价 | 底部放量（量比>2） | ? | 0~2 |
| 量价 | VWAP支撑 | ? | 0~1 |
| 资金 | 主力净流入 | ? | 0~2 |
| 趋势强度 | ADX>25且+DI>-DI | ? | 0~1 |
总分及操作建议：
- ≥15分 → 重仓；12
14分 → 中仓；911分 → 轻仓；<9分 → 观望
2.9 技术分析总结输出
📊 缠论技术面评分：X/10
当前趋势（日线）：[上涨/下跌/震荡]
当前趋势（周线）：[上涨/下跌/震荡]
当前结构：[一买/二买/三买/一卖/二卖/三卖/中枢震荡]
均线状态：[多头排列/空头排列/均线粘合]
动量状态：RSI=XX | KDJ金叉/死叉 | CCI=XX
波动率：BOLL位置=[上轨/中轨/下轨] | ATR=XX
量价：OBV趋势=[上升/下降/背离] | 近日量比=X.X
资金：主力5日净流入=[+XX亿/−XX亿]
多指标共振评分：XX/23分
关键支撑位：XX.XX 元（来源：XX）
关键压力位：XX.XX 元（来源：XX）
ATR动态止损：XX.XX 元
技术信号：[买入/看多/中性/看空/卖出]Show full SKILL.md (158 more words)Show less
🔴 阶段3：基本面分析
参考文件：references/financial-analysis.md
3.1 盈利能力
计算并展示（最新3~4个报告期趋势）：
- 毛利率、净利率趋势
- ROE（及杜邦分解）
- 扣非净利润增速
- 核心结论：盈利能力处于行业什么水平？是否在改善？
3.2 成长能力
- 营收/净利润3年CAGR
- 最新季度同比/环比增速
- 研发投入（若适用）
- 核心结论：是否处于成长期？成长质量如何？
3.3 财务健康度
- 资产负债率、流动比率、速动比率
- 经营现金流 / 净利润比率（盈利含金量）
- 自由现金流（FCF）
- 红旗信号检查（参见
references/financial-analysis.md第七节） - 核心结论：财务是否稳健？有无风险信号？
3.4 基本面总结输出
📈 基本面评分：X/10
盈利能力：[优秀/良好/一般/较差]
成长性：[高成长/稳定成长/成长放缓/衰退]
财务健康：[稳健/良好/需关注/风险较高]
核心优势：...
核心风险：...🔴 阶段4：估值分析
参考文件：references/valuation.md
4.1 相对估值
- 当前 P/E(TTM)、P/B、EV/EBITDA
- 历史估值百分位（近3年历史区间）
- 同行业可比公司估值对比（调用同行业数据）
- 得出相对估值结论：低估/合理/高估
4.2 PEG分析（成长股）
- PEG = P/E(TTM) / 净利润增速
- PEG < 1 低估，1~2 合理，>2 高估
4.3 简化DCF估值
基于过去3年FCF均值和预测增速，计算合理价值区间：
- 乐观/基准/悲观三种情景
- 给出每股内在价值估算区间
4.4 估值总结输出
💰 估值评分：X/10
当前PE(TTM)：XX× （历史分位数：XX%）
当前PB：XX×
EV/EBITDA：XX×
相对同行：[低估XX%/合理/高估XX%]
DCF内在价值区间：XX.XX ~ XX.XX 元（当前价格：XX.XX）
估值结论：[严重低估/低估/合理/高估/严重高估]🔴 阶段5：综合研究报告输出
输出顺序：先生成 Markdown 报告文件（.md），再按阶段6流程自动生成 PDF。
输出完整Markdown格式报告，结构如下：
重要规范：报告第一章必须是「📋 总体结论与投资建议」，在所有详细章节之前，作为全篇摘要。读者可只看此章节即获得核心判断，后续章节为支撑论据。
# [公司名称]（股票代码）综合投研报告
**报告日期**：YYYY年MM月DD日
**分析基准价格**：XX.XX 元（XX月XX日收盘价）
**当前市值**：XXX 亿元
---
## 📋 总体结论与投资建议
> 本节为全篇核心摘要，其余章节为详细支撑论据，建议先阅读本节再按需查阅后续内容。
### 综合评级：[简明评级描述，如"谨慎观望，等待右侧信号确认后逢低分批布局"]
### 【一句话结论】
[100字以内的核心判断，说明技术面现状 + 基本面优势 + 操作建议]
### 【总体情况五维评分】
| 维度 | 评分（星级/5） | 核心结论 |
|------|--------------|---------|
| 技术面 | ★★☆☆☆ 2/5 | [当前技术信号概要] |
| 基本面 | ★★★★☆ 4/5 | [财务健康状况概要] |
| 估值面 | ★★★☆☆ 3/5 | [PE/PB所处历史区间] |
| 资金面 | ★★☆☆☆ 2/5 | [资金流向及机构持仓] |
| 情绪面 | ★★★☆☆ 3/5 | [市场情绪与主题热度] |
| **综合共振** | **X / 100** | [当前整体判断] |
### 【后续操作建议】
**短期（0~2周）**：[具体操作指导，含关键支撑/压力位和止损线]
**中期（1~3个月）**：[目标价区间与加仓条件]
**长期（6个月以上）**：[战略性配置建议及仓位比例]
### 【主要风险提示】
| 风险类型 | 具体内容 |
|---------|---------|
| 下行风险 | [跌破关键支撑后的下探目标] |
| 宏观风险 | [宏观/政策层面风险] |
| 行业风险 | [行业竞争/政策层面风险] |
| 估值风险 | [估值层面风险] |
---
## 一、公司概况
## 二、技术分析（缠论 + 多指标共振）
## 三、基本面分析
## 四、估值分析
## 五、综合结论与操作建议
## 六、数据来源
⚠️ **免责声明**：本报告仅供参考，不构成投资建议。投资有风险，决策需谨慎。🔴 阶段6：PDF 报告生成
在 Markdown 报告生成完成后，立即执行以下步骤，将报告转换为专业排版 PDF。
6.1 环境检查与依赖安装
import importlib, subprocess, sys
try:
importlib.import_module("reportlab")
except ImportError:
subprocess.check_call([sys.executable, "-m", "pip", "install", "reportlab", "-q"])6.2 中文字体检测（按优先级查找）
C:\Windows\Fonts\msyh.ttc（微软雅黑，Windows 首选）C:\Windows\Fonts\simhei.ttf（黑体，Windows 备选）/System/Library/Fonts/PingFang.ttc（macOS 苹方）/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc（Linux）
6.3 PDF 输出规范
- 文件命名：
{公司名称}投研报告_{YYYYMMDD}.pdf - 保存路径：与 Markdown 报告同目录
- 页面规格：A4，左右边距 20mm，上下边距 20mm
- 必须包含：封面摘要表、页眉（公司名+日期）、页脚（页码+免责声明）、多级标题、数据表格、风险警告段落
颜色方案：
- 主色：
#003087（深蓝）| 辅色：#1a4a8a（中蓝） - 警告：
#cc4400（红棕）| 风险表头：#8b1a1a（深红）| 买入表头：#1a6b3a（深绿）
6.4 生成脚本结构（写入独立 .py 文件执行，避免命令行字符限制）
# 文件名：generate_pdf_report.py
# 执行：python generate_pdf_report.py
# 核心模块：
# register_fonts() → 注册中文字体
# build_styles() → 定义全套段落样式
# table_style() → 返回统一表格 TableStyle
# build_story() → 按章节构建 story 列表
# header_footer() → 页眉页脚回调
# main() → 组装并输出 PDF配置选项
| 配置项 | 说明 | 默认值 |
|---|---|---|
| 日线K线数量 | 用于缠论分析的历史日线数量 | 250根 |
| 周线K线数量 | 用于周线趋势验证 | 104根 |
| 财报期数 | 用于趋势分析的历史报告期数 | 近4期 |
| PDF输出 | 是否自动生成PDF报告 | 是 |
错误处理
- 接口调用失败：明确告知用户哪些数据无法获取，不得凭空捏造数据
- K线数量不足（< 100根）：降级分析，如实说明局限性
- 财报未披露：使用最近已披露的报告期，并在报告中注明
- PDF生成失败：提示用户安装
reportlab（pip install reportlab）
安全注意
⚠️ 风险提示
- 缠论分析基于程序化规则，在复杂走势中存在主观性，结论仅供参考
- 所有分析数据基于历史行情，不代表未来表现
- 本技能输出内容不构成投资建议，投资者需自行承担投资风险
- 不在分析结果中硬编码 API Key 或任何敏感信息
隐私保护
- 所有股票数据通过官方公开接口获取
- 不存储用户查询的股票代码或分析结果到外部服务
相关文件
references/chan-theory.md- 缠论理论完整参考，含中枢/笔/背驰/买卖点规则及多指标共振评分系统references/financial-analysis.md- 财务分析框架，含盈利/成长/健康度分析方法及红旗信号检查清单references/valuation.md- 估值分析方法，含PE/PB/EV/DCF/PEG多维估值模型
依赖说明
本技能依赖以下外部技能，需提前安装：
finance-data-retrieval（必需）：提供 Tushare 行情、财务、资金数据接口- 需要配置 Tushare Token（
TUSHARE_TOKEN环境变量）
- 需要配置 Tushare Token（
Python 依赖（运行时自动安装）：
reportlab：PDF 生成库
© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 7 other files (references, assets) in skills/chanlun-stock-analysis of LeoYeAI/openclaw-master-skills.
- SKILL.md
- CHANGELOG.md
- README.md
- _meta.json
- assets/README.md
- references/chan-theory.md
- references/financial-analysis.md
- references/valuation.md
Open the folder on GitHubat commit e5199b5
Compare with similar skills
Chan Stock Analysis 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 |
|---|---|---|---|---|---|---|
| Chan Stock Analysis this skillLeoYeAI/openclaw-master-skills | 2.2k | — | ~2.4k | Automated safety check: Pass | MIT | |
| Stock APIzhangxiangliang/stock-api | 2k | — | ~507 | Automated safety check: Pass | MIT | |
| Tushare Datazillionare/zillionare | 322 | 2 repos | ~2.3k | Automated safety check: Pass | None | |
| Tradingview MCPatilaahmettaner/tradingview-mcp | 5k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Digital Oraclekomako-workshop/digital-oracle | 878 | — | ~5.9k | Automated safety check: Pass | MIT | |
| Longbridge Researchhelsome/folio | 271 | 3 repos | ~2.1k | Automated safety check: Pass | MIT |
Similar skills
Tushare Data
zillionare/zillionare
面向中文自然语言的 Tushare 数据研究技能。用于把“看看这只股票最近怎么样”“帮我查财报趋势”“最近哪个板块最强”“北向资金在买什么”“给我导出一份行情数据”这类请求，转成可执行的数据获取、清洗、对比、筛选、导出与简要分析流程。适用于 A 股、指数、ETF/基金、财务、估值、资金流、公告新闻、板块概念与宏观数据等研究场景。
Tradingview MCP
atilaahmettaner/tradingview-mcp
AI Trading Intelligence — live prices, 30+ technical indicators, backtesting (6 strategies), walk-forward overfitting detection, trade logs, equity curves, licensed news sentiment (Marketaux), and…
Digital Oracle
komako-workshop/digital-oracle
Answer prediction questions using market trading data, not opinions.
Longbridge Research
helsome/folio
Institution ratings, consensus price targets, EPS/revenue forecasts, finance calendar, shareholder data, fund holders, insider trades (SEC Form 4), short interest, industry rankings, peer group…
Longbridge Earnings
helsome/folio
Earnings analysis — pre- and post-earnings. An agent skill from helsome/folio.
More from LeoYeAI/openclaw-master-skills
All 1,200 skills in this repoDevOps Pipeline Management
LeoYeAI/openclaw-master-skills
Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.
Feishu Document Collaboration
LeoYeAI/openclaw-master-skills
Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.
Files Memory System
LeoYeAI/openclaw-master-skills
Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.
GEO-Claw AI Visibility Agent
LeoYeAI/openclaw-master-skills
Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.
Google Workspace CLI
LeoYeAI/openclaw-master-skills
Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.
HealthFit Health Advisors
LeoYeAI/openclaw-master-skills
Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.
Related
Categories
Questions about Chan Stock Analysis
What does Chan Stock Analysis do?
缠论+基本面+财报+估值综合股票分析技能，生成专业投研报告（含 PDF）. An agent skill from LeoYeAI/openclaw-master-skills. Chan Stock Analysis is an agent skill from LeoYeAI/openclaw-master-skills.
When should I use Chan Stock Analysis?
Chan Stock Analysis fits situations like: : 用户提供股票代码，要求进行深度股票分析、缠论技术分析、基本面研究、财报解读、估值分析、综合投研报告; tasks that involve Stock and market analysis.
How do I install Chan Stock Analysis in Claude Code?
Run `npx skills add LeoYeAI/openclaw-master-skills --skill chan-stock-analysis -a claude-code`. Or copy the skill folder (skills/chanlun-stock-analysis in LeoYeAI/openclaw-master-skills) into .claude/skills/chan-stock-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Chan Stock Analysis in Codex?
Run `npx skills add LeoYeAI/openclaw-master-skills --skill chan-stock-analysis -a codex`. Or copy the skill folder (skills/chanlun-stock-analysis in LeoYeAI/openclaw-master-skills) into .agents/skills/chan-stock-analysis in your project. Codex loads it when a task matches its description.
Can I use Chan Stock Analysis in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill chan-stock-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/chan-stock-analysis, .gemini/skills/chan-stock-analysis, .github/skills/chan-stock-analysis and .opencode/skills/chan-stock-analysis in your project.
What does Chan Stock Analysis need to run?
Going by SKILL.md and its folder, Chan Stock Analysis needs the command-line tools its instructions call (pip) and credentials named TUSHARE_TOKEN.
Does Chan Stock Analysis access the network?
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Chan Stock Analysis safe to install?
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.
What licence does Chan Stock Analysis use?
Chan Stock Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Chan Stock Analysis use?
About 2.4k tokens (SKILL.md is roughly 9.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.6k tokens, read only when the agent opens those files.
What are the alternatives to Chan Stock Analysis?
Skills that share tags, products or a category with Chan Stock Analysis: Stock API (zhangxiangliang/stock-api, 2k stars), Tushare Data (zillionare/zillionare, 322 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars) and Digital Oracle (komako-workshop/digital-oracle, 878 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Chan Stock Analysis?
LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.
Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.