What makes Stock Analysis notable?

1.3K downloads. Trust evidence available

How should Stock Analysis be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Stock Analysis

提供A股个股及市场多维度深度分析，涵盖基本面、资金面、技术面、筹码和舆情，给出评分及买卖操作建议。 Skill: Stock Analysis Owner: derrors Summary: 提供A股个股及市场多维度深度分析，涵盖基本面、资金面、技术面、筹码和舆情，给出评分及买卖操作建议。 Tags: latest:1.0.9 Version history: v1.0.9 | 2026-04-22T02:08:51.064Z | auto - Pytdx 数据源被移除，精简为妙想金融、Efinance、AkShare 三级自动容灾。 - 妙想金融资讯正文将直接传递给 LLM 作为分析输入，辅助生成分析摘要和投资结论。 - SKILL.md 说明文档同步更新，优化并明确各数据源优先级及失效容灾逻辑。 - 依赖和主要脚本同步调整，确保移除 Pytdx 后运行和数据采集逻辑正常。 - 输出 json 字段和样例简化说明，将资讯摘要命名更通用，并统一 LLM 分析入口。 v1.0.8 | 2026-04-21T10:48:20.53

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.3k

Updated

Oct 10, 2026

Version

1.0.9

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.3K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.3K downloadsadoption · observed Oct 10, 2026
Latest release: 1.0.9release · observed Apr 22, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17a2g9ec3f6zcpwkg0p441gc98599nv:stock-analysis-report

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-derrors-stock-analysis-report/snapshot"

Documentation

CLAWHUB

156,494 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---

name: stock-analysis
description: |
  A股市场分析与个股深度分析技能。支持基本面（财务指标/估值分位）、资金面（主力资金/DDX/DDY/DDZ）、技术面（均线/乖离率/量比）、筹码分布、舆情情报（新闻/研报/公告）等多维度分析，输出结构化评分与操作建议。

Triggers: "分析股票", "个股分析", "市场分析", "A股分析", "stock analysis", "analyze stock", "market analysis", "股票评分", "买卖建议", "涨停分析"

Does NOT trigger:

- 简单的股价查询（无需深度分析）
- 港股/美股/非A股市场分析
- 基金/债券/期货分析

Output: 结构化分析报告（评分0-100、操作方向、买卖点位、风险提示、检查清单）
version: 1.0.9
license: MIT-0
metadata:
  openclaw:
    requires:
      env:
        - LLM_API_KEY
        - LLM_BASE_URL
        - LLM_MODEL
      bins:
        - python3
    optional:
      env:
        - MX_APIKEY
        - SERPAPI_KEY
        - TAVILY_KEY
        - BRAVE_KEY
        - BOCHA_KEY
        - BIAS_THRESHOLD
        - NEWS_MAX_AGE_DAYS
        - ENABLE_CHIP
        - LOG_LEVEL
    primaryEnv: LLM_API_KEY
    emoji: "📈"
    install:
      - kind: uv
        command: pip install -r requirements.txt

---

# A股股票市场分析 Skill

## 功能

### 个股分析

输入股票代码，输出结构化分析结果：

- **基本面**：净利润、营收、ROE、毛利率、资产负债率、机构持股比例、盈利预测
- **估值**：PE(TTM)、PB、历史分位
- **资金面**：主力资金流向（超大单/大单/中单/小单净额）、DDX/DDY/DDZ 指标
- **技术面**：MA5/MA10/MA20/MA60 均线、多头排列、乖离率、量比
- **筹码分布**：获利比例、平均成本、集中度
- **舆情情报**：妙想金融资讯（新闻/研报/公告，LLM 分析）+ 多引擎新闻搜索
- **实时行情**：当前价、涨跌幅、成交量、换手率
- **分析结论**：评分 + 操作方向 + 买卖点位 + 检查清单 + 风险提示

### 市场分析

每日 A 股市场复盘：

- 主要指数（上证/深证/创业板）
- 涨跌统计（涨跌家数、涨停跌停数）
- 板块排名（领涨/领跌 Top5）
- 市场情绪判断 + 操作建议

## 使用方式

### 生成分析报告（推荐）

```bash
# 个股分析报告 → 保存到 reports/{代码}_{日期}.md
python3 {baseDir}/scripts/report.py stock 600519

# 市场分析报告 → 保存到 reports/market_{日期}.md
python3 {baseDir}/scripts/report.py market

# 同时输出 JSON
python3 {baseDir}/scripts/report.py stock 600519 --json

# 自定义输出目录
python3 {baseDir}/scripts/report.py stock 600519 -o ./my-reports
```

### JSON 输出

```bash
python3 {baseDir}/scripts/analyze_stock.py 600519
python3 {baseDir}/scripts/analyze_market.py
```

### Handler 调用

```python
from src.index import handler
result = await handler({"mode": "stock", "code": "600519"})
result = await handler({"mode": "market"})
result = await handler({"mode": "stock", "code": "600519", "save": True})
result = await handler({"mode": "stock", "code": "600519", "save": True, "output_dir": "./reports"})
```

## 输入格式

| 字段          | 类型      | 必填            | 说明                            |
| ----------- | ------- | ------------- | ----------------------------- |
| mode        | string  | 是             | "stock" 或 "market"            |
| code        | string  | mode=stock时必填 | A股股票代码，如 "600519"             |
| save        | boolean | 否             | 是否保存 Markdown 报告到 reports/ 目录 |
| output_dir | string  | 否             | 自定义报告输出目录（需 save=true）        |

## 输出格式

### 个股分析结果

```json
{
  "stock_code": "600519",
  "stock_name": "贵州茅台",
  "core_conclusion": "一句话核心结论",
  "score": 75,
  "action": "买入/观望/卖出",
  "trend": "看多/震荡/看空",
  "buy_price": 1800.0,
  "stop_loss_price": 1700.0,
  "target_price": 2000.0,
  "checklist": [{"condition": "...", "status": "✅/❌", "detail": "..."}],
  "risk_alerts": ["风险1", "风险2"],
  "positive_catalyst

README.md

<div align="center">

# 📈 A 股股票市场分析 Skill

专为 OpenClaw 等智能体设计的 A 股股票分析技能

[![License: MIT-0](https://img.shields.io/badge/License-MIT--0-yellow.svg)](LICENSE)
[![Python 3.9+](https://img.shields.io/badge/Python-3.9%2B-blue.svg)](https://www.python.org/)
[![OpenClaw Skill](https://img.shields.io/badge/OpenClaw-Skill-green.svg)](https://github.com/openclaw)

基于 [daily\_stock\_analysis](https://github.com/ZhuLinsen/daily_stock_analysis) 项目精简重写，去除 WebUI、通知推送、Agent 问股等非核心功能，聚焦分析能力本身。

</div>

***

## ✨ 功能特性

### 📊 个股分析

输入股票代码，输出结构化分析结果：

- **技术面分析**：MA5/MA10/MA20/MA60 均线、多头排列判断、乖离率、量比
- **筹码分布**：获利比例、平均成本、集中度
- **舆情情报**：妙想金融资讯（新闻/研报/公告，LLM 分析）+ 多引擎新闻搜索
- **实时行情**：当前价、涨跌幅、成交量、换手率等
- **分析结论**：一句话核心结论 + 评分 + 操作方向 + 精确买卖点位 + 操作检查清单 + 买卖策略

### 🌐 市场分析

每日 A 股市场复盘：

- **主要指数**：上证指数、深证成指、创业板指
- **市场统计**：涨跌家数、涨停跌停数
- **板块排名**：领涨 / 领跌板块 Top5
- **分析结论**：市场情绪判断 + 操作建议 + 完整复盘报告

### 🔄 多源数据架构

#### 推荐配置：妙想金融

配置 `MX_APIKEY` 后，妙想金融自动成为行情数据、财务/资金/估值、资讯搜索的**最高优先级数据源**，覆盖能力最全、数据质量最高。推荐优先配置。

👉 前往 [妙想 Skills 页面](https://dl.dfcfs.com/m/itc4) 获取 API Key

#### 行情数据采用自动容灾策略：

| 优先级 | 数据源          | 说明                          |    需要 Token   |
| :-: | ------------ | --------------------------- | :-----------: |
|  0  | **妙想金融**     | 东财妙想 API，覆盖行情 + 财务数据        | ✅ `MX_APIKEY` |
|  1  | **Efinance** | 基于东财接口，覆盖日 K、实时行情、板块排名、市场统计 |       ❌       |
|  2  | **AkShare**  | 东财 + 新浪双通道，额外支持筹码分布         |       ❌       |

> - 配置 `MX_APIKEY` 后妙想自动成为最高优先级；未配置时从 Efinance 开始
> - 任意数据源异常时自动切换到下一级，无需人工干预

## 🚀 快速开始

### 方式一：通过 ClawHub 安装（推荐）

使用 OpenClaw CLI 一键安装：

```bash
openclaw skill install stock-analysis-report
```

安装后即可在 OpenClaw 中直接使用：

```
分析贵州茅台
市场分析
```

### 方式二：本地开发

#### 1. 安装依赖

```bash
pip install -r requirements.txt
```

#### 2. 配置环境变量

```bash
cp .env.example .env
```

编辑 `.env` 文件，填入你的 API Key：

```env
# LLM 配置（必填）— 支持 DeepSeek 和 OpenAI 兼容模型
LLM_BASE_URL=https://api.deepseek.com/v1
LLM_API_KEY=your-api-key-here
LLM_MODEL=deepseek-chat

# 妙想金融数据（可选，配置后自动成为第一优先级数据源 + 资讯搜索源）
MX_APIKEY=

# 新闻搜索（至少配置一个，可选）
SERPAPI_KEY=
TAVILY_KEY=
BRAVE_KEY=
BOCHA_KEY=
```

> 💡 行情数据源（Efinance / AkShare）均为免费接口，无需配置任何 Token。

#### 3. 调用分析

#### 生成 Markdown 报告（推荐）

```bash
# 个股分析报告 → reports/{代码}_{日期}.md
python3 scripts/report.py stock 600519

# 市场分析报告 → reports/market_{日期}.md
python3 scripts/report.py market

# 同时输出 JSON
python3 scripts/report.py stock 600519 --json

# 自定义输出目录
python3 scripts/report.py stock 600519 -o ./my-reports
```

#### JSON 输出

```bash
python3 scripts/analyze_stock.py 600519    # 个股分析
python3 scripts/analyze_market.py          # 市场分析
```

#### Python API

```python
import asyncio
from src.index import analyze_stock, analyze_market

# 个股分析 + 保存报告
result = asyncio.run(analyze_stock("600519", save=True))
print(result.core_conclusion)   # 一句话核心结论
print(result.action)            # 买入/观望/卖出

# 市场分析 + 保存报告
result = asyncio.run(analyze_market(save=True))
print(result.sentiment)         # 偏多/中性/偏空
```

#### OpenClaw Handler

```python
from src.index import handler

resu

_meta.json

{
  "ownerId": "kn7da87j1vga39tq7bxyc830gh834079",
  "slug": "stock-analysis-report",
  "version": "1.0.9",
  "publishedAt": 1776823731064
}

skill-card.md

## Description:

Analyzes A-share stocks and the broader A-share market across fundamentals, valuation, capital flows, technical indicators, chip distribution, and news or research signals to produce structured scores and operating suggestions.

This skill is ready for commercial/non-commercial use.

## Publisher:

[derrors](https://clawhub.ai/user/derrors)

### License/Terms of Use:

MIT-0

## Use Case:

External users and developers use this skill to generate A-share stock deep-dive reports or daily A-share market reviews with structured conclusions, risk alerts, and suggested trading posture. It is intended for analysis support only and the artifact states that results are not investment advice.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: A caller-controlled LLM endpoint could expose the configured LLM API key or send market, news, and prompt content to an unintended provider.

Mitigation: Install only in a trusted environment, restrict allowed LLM endpoints, and do not expose the handler to untrusted callers until configuration fields are allowlisted.

Risk: Saved reports may be written outside the intended reports folder when an unsafe output path is accepted.

Mitigation: Keep saved report paths under a known reports directory and validate or constrain output_dir before enabling report persistence.

Risk: Market data, news content, and user prompts may be transmitted to configured LLM and search providers.

Mitigation: Review configured providers, keys, and data-sharing expectations before use, and treat generated investment analysis as support material rather than financial advice.

Risk: Unpinned Python dependencies can change behavior across installs.

Mitigation: Pin dependency versions and review dependency updates before deployment.

## Reference(s):

- [ClawHub Skill Page](https://clawhub.ai/derrors/skills/stock-analysis-report)
- [Miaoxiang Skills Page](https://dl.dfcfs.com/m/itc4)

## Skill Output:

**Output Type(s):** [Analysis, Markdown, JSON, Files, Guidance]

**Output Format:** [Markdown reports and JSON objects with stock or market analysis fields]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Can save reports locally when requested; outputs include disclaimers and may include scores, suggested action, price levels, risk alerts, checklist items, news summaries, and raw LLM report text.]

## Skill Version(s):

1.0.9 (source: server release metadata, SKILL.md frontmatter, manifest.yaml)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

config.example.yaml

# LLM 配置（必填）
llm_base_url: "https://api.deepseek.com/v1"
llm_api_key: "your-api-key-here"
llm_model: "deepseek-chat"

# 新闻搜索（至少配置一个）
serpapi_key: ""
tavily_key: ""
brave_key: ""
bocha_key: ""

# 妙想金融数据源（可选）— 配置后自动成为第一优先级
mx_apikey: ""

# 分析参数
bias_threshold: 5.0
news_max_age_days: 3
enable_chip: true

# 日志级别：DEBUG / INFO / WARNING / ERROR
log_level: "INFO"

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