What makes stock-diagnosis notable?

2.1K downloads. Trust evidence available

How should stock-diagnosis 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-diagnosis

面向沪深京A股的单票综合诊断能力。适用于用户提出“这只股票整体怎么样”“是否值得继续持有/加仓/减仓”“当前风险和机会如何”等泛化问题时，返回结构化的Markdown诊断报告。每次仅分析一只股票，不处理港股/美股及多标的对比。触发核心条件：用户问法为概括性诊断，未指定某个单一技术指标或财务指标（如MACD、RSI... Skill: stock-diagnosis Owner: financial-ai-analyst Summary: 面向沪深京A股的单票综合诊断能力。适用于用户提出“这只股票整体怎么样”“是否值得继续持有/加仓/减仓”“当前风险和机会如何”等泛化问题时，返回结构化的Markdown诊断报告。每次仅分析一只股票，不处理港股/美股及多标的对比。触发核心条件：用户问法为概括性诊断，未指定某个单一技术指标或财务指标（如MACD、RSI... Tags: latest:1.0.0 Version history: v1.0.0 | 2026-04-17T11:19:28.071Z | user Publish 1.0.0 Archive index: Archive v1.0.0: 4 files, 7396 bytes Files: scripts/get_data.py (11010b), skill-card.md (2373b

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

2.1k

Updated

Oct 9, 2026

Version

1.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 2.1K downloads reported by the source. Last updated 10/9/2026.

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 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 2.1K downloadsadoption · observed Oct 9, 2026
Latest release: 1.0.0release · observed Apr 17, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s172qfps754dhtdynwv0gwshes83mtd4:stock-diagnosis

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
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-financial-ai-analyst-stock-diagnosis/snapshot"

Documentation

CLAWHUB

5,845 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: stock-diagnosis
description: 面向沪深京A股的单票综合诊断能力。适用于用户提出“这只股票整体怎么样”“是否值得继续持有/加仓/减仓”“当前风险和机会如何”等泛化问题时，返回结构化的Markdown诊断报告。每次仅分析一只股票，不处理港股/美股及多标的对比。触发核心条件：用户问法为概括性诊断，未指定某个单一技术指标或财务指标（如MACD、RSI、ROE等）做精确计算。
metadata:
  {
    "openclaw": {
      "requires": {
        "env":["EM_API_KEY"]
      }
    }
  }
---

# 股票综合诊断

通过**自然语言问句**对单只A股进行综合分析，返回 Markdown 诊断报告，适用场景包括：
- **个股整体判断（基本面 + 资金面 + 风险面）**
- **持仓决策参考（持有/减仓/止盈/观望）**
- **热点行情下的个股风险排查**
- **用户泛化问法的一站式诊断回答**

## 密钥来源与安全说明

- 本技能仅使用一个环境变量：`EM_API_KEY`。
- `EM_API_KEY` 由东方财富妙想服务（`https://ai.eastmoney.com/mxClaw`）签发，用于接口鉴权。
- 在提供密钥前，请先确认密钥来源、可用范围、有效期及是否支持重置/撤销。
- 禁止在代码、提示词、日志或输出文件中硬编码/明文暴露密钥。

## 功能范围

### 基础诊断能力
- 输入自然语言问句，调用诊股接口生成结构化结论
- 每次仅处理**一只**沪深京A股股票
- 返回可读 Markdown 报告（优先提取 `data.displayData`）
- 支持将结果保存为本地 `.md` 文件，便于复盘追踪

### 触发规则（何时使用本技能）
- 用户问题是**笼统/概括性**诊断：如“这只股票怎么样”“值得买吗”“该不该卖”
- 问句中未明确要求计算单个技术指标或财务指标
- 若上下文已明确股票实体，用户后续使用“它/这只股票”等代词继续提问，也应触发

### 不触发规则（何时不要使用本技能）
- 用户明确点名具体指标计算：MACD、KDJ、RSI、布林带、ROE、PE 等
- 用户要求多只股票横向对比（应走多标的分析类能力）
- 用户咨询港股、美股或其他非A股市场

### 触发示例

| 触发（泛化诊断） | 不触发（指标定向） |
|---|---|
| 丹化科技怎么样？ | 丹化科技的MACD出现金叉了吗？ |
| 海康威视亏了怎么操作？ | 海康威视当前市盈率是多少？ |
| 华尔泰值得投资吗？ | 华尔泰的RSI是否超买？ |
| 全面分析一下中国平安 | 中国平安的ROE趋势如何？ |

## 前提条件

### 1. 注册东方财富妙想账号

访问 https://ai.eastmoney.com/mxClaw 注册账号并获取 API Key。

### 2. 配置 Token

```bash
# macOS 添加到 ~/.zshrc，Linux 添加到 ~/.bashrc
export EM_API_KEY="your_api_key_here"
```

然后根据系统执行对应的命令：

**macOS：**
```bash
source ~/.zshrc
```

**Linux：**
```bash
source ~/.bashrc
```

## 快速开始

### 1. 命令行调用

```bash
python3 {baseDir}/scripts/get_data.py --query "东方财富股票咋样"
```

**输出示例**
```text
Saved: /path/to/workspace/stock_diagnosis/stock_diagnosis_90bf169c.md
（随后输出 Markdown 诊断内容）
```

**参数说明：**

| 参数 | 说明 | 必填 |
|---|---|---|
| `--query` | 用户原始自然语言问句 | ✅（`--query` 或 stdin 二选一） |
| `--no-save` | 仅输出结果，不写入本地文件 | 否 |

### 2. 代码调用

```python
import asyncio
from pathlib import Path
from scripts.get_data import diagnose_stock

async def main():
    result = await diagnose_stock(
        question="分析一下东方财富这只股票",
        output_dir=Path("workspace/stock_diagnosis"),
        save_to_file=True,
    )
    if "error" in result:
        print(result["error"])
    else:
        print(result["content"])
        if result.get("output_path"):
            print("已保存至:", result["output_path"])

asyncio.run(main())
```

## 输出规范
通过脚本或工具拿到诊股结果后，**对用户的可见回复必须以接口返回的 Markdown 正文为主体**，避免模型二次转述。仅当接口/脚本明确返回 `error`、或正文为空时，才用简短文字说明失败原因；**禁止**在失败时杜撰报告内容。

## 常见问题

**错误：EM_API_KEY is required.**  
→ 需先配置 `EM_API_KEY`，请联系官网获取并手动配置。

**为什么需要保持原始问句？**  
→ 诊股接口依赖用户自然语言上下文，建议避免改写导致语义偏移。

**如何只看输出，不落盘？**
```bash
python3 -m scripts.get_data --query "东方财富股票咋样" --no-save
```

## 合规说明

- 诊股结果仅供参考，不构成投资建议，输出时应附风险提示。
- 禁止在代码或提示词中硬编码账号 ID、会话 ID 或 token。
- 环境变量按敏感信息处理，不在日志或回复中泄露。
- 接口失败时不得编造结论，应返回明确错误或不确定性说明。

_meta.json

{
  "ownerId": "kn7b4ptpdag877t9kmq8axyja182taab",
  "slug": "stock-diagnosis",
  "version": "1.0.0",
  "publishedAt": 1776424768071
}

skill-card.md

## Description:

Provides single-stock comprehensive diagnosis for Shanghai, Shenzhen, and Beijing A-share equities from natural-language questions, returning structured Markdown reports for broad questions about overall outlook, holding decisions, risks, and opportunities.

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

## Publisher:

[financial-ai-analyst](https://clawhub.ai/user/financial-ai-analyst)

### License/Terms of Use:

MIT-0

## Use Case:

External users and developers use this skill to request a concise diagnosis of one mainland China A-share stock from a broad natural-language question. It is intended for single-stock review and decision support, not for multi-stock comparison, non-A-share markets, or precise calculation of a named indicator.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Stock questions are sent to Eastmoney's service using EM_API_KEY.

Mitigation: Use a revocable, scoped key where available and avoid including sensitive personal context in stock questions.

Risk: Markdown diagnosis reports may be saved locally by default.

Mitigation: Run with --no-save when local report retention is not desired.

Risk: The report may be mistaken for investment advice.

Mitigation: Keep the skill's risk notice visible and treat outputs as reference information rather than financial advice.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/financial-ai-analyst/skills/stock-diagnosis)
- [Eastmoney Miaoxiang service](https://ai.eastmoney.com/mxClaw)
- [Eastmoney stock analysis API base](https://ai-saas.eastmoney.com/proxy/)

## Skill Output:

**Output Type(s):** [Text, Markdown, Code, Shell commands, Configuration]

**Output Format:** [Markdown report text, with optional saved .md files and command-line or Python usage examples]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Requires EM_API_KEY; accepts one natural-language stock question through --query or stdin; --no-save prevents local Markdown report retention.]

## Skill Version(s):

1.0.0 (source: server release metadata)

## 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.

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