What makes 短线手术刀 (ScalpelTrade) notable?

1.1K downloads. Trust evidence available

How should 短线手术刀 (ScalpelTrade) 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

短线手术刀 (ScalpelTrade)

A股短线量化分析工具 — 实时行情、9因子选股、多空辩论+风控审查、推荐追踪闭环。数据源：新浪财经+东方财富（免费行情）。 Skill: 短线手术刀 (ScalpelTrade) Owner: zhubohan190601-crypto Summary: A股短线量化分析工具 — 实时行情、9因子选股、多空辩论+风控审查、推荐追踪闭环。数据源：新浪财经+东方财富（免费行情）。 Tags: a-shares:2.2.0, china-stocks:2.2.0, debate-analysis:2.0.0, finance:2.2.0, latest:2.2.0, market-data:2.2.0, multi-agent:2.2.0, stock-screening:2.2.0 Version history: v2.2.0 | 2026-06-11T14:10:26.985Z | user v2.2统一发版: 更名+9因子+风控审查+分歧转一致+推荐追踪闭环+东方财富资金流数据源+多日趋势分析+假跌破检测 v2.1.4 | 2026-06-11T1

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.1k

Updated

Oct 11, 2026

Version

2.2.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.1K downloads reported by the source. Last updated 10/11/2026.

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 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1.1K downloadsadoption · observed Oct 11, 2026
Latest release: 2.2.0release · observed Jun 11, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17fkaq9am9e7y71qpazk0seh987w6es:finbot-stock

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-zhubohan190601-crypto-finbot-stock/snapshot"

Documentation

CLAWHUB

44,581 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: 短线手术刀 (ScalpelTrade)
description: "A股短线量化分析工具 — 实时行情、9因子选股、多空辩论+风控审查、推荐追踪闭环。数据源：新浪财经+东方财富（免费行情）。"
tags:
  - finance
  - china-stocks
  - a-shares
  - market-data
  - stock-screening
  - multi-agent
  - debate-analysis
version: 2.2.0
---

# 短线手术刀 (ScalpelTrade) v2.2 — A股短线多因子量化分析工具

专为A股短线交易设计的多Agent量化分析框架。四层架构（采集→分析→辩论→追踪），提供从数据采集到推荐闭环的全链路支持。

## 架构

```
         ┌──────────────────────────────────────────┐
Layer 4  │  追踪层: tracker.py                      │
         │  推荐记录 → 每日检查 → 报告生成           │
         ├──────────────────────────────────────────┤
Layer 3  │  决策层: debater.py                      │
         │  多头×空头辩论 → 风控审查 → 分歧转一致检测  │
         ├──────────────────────────────────────────┤
Layer 2  │  分析层: analyzer.py                     │
         │  多日趋势分析、假跌破检测、因子评分         │
         ├──────────────────────────────────────────┤
Layer 1  │  执行层: fetcher.py                      │
         │  实时行情(新浪) + 资金流向(东方财富) +     │
         │  9项技术因子(RSI/MACD/KDJ/布林/ICU等)     │
         └──────────────────────────────────────────┘
```

## 用法

### Layer 1: 数据层

#### 单只实时行情
```bash
python3 {baseDir}/scripts/fetcher.py
```
返回结构化数据：price、change_pct、high、low、amount_yi、volume_wan

#### 批量行情
```python
from scripts.fetcher import fetch_batch
results = fetch_batch(["000001","000002","600519"])
```

#### 技术指标计算（v2.2 — 9个因子）
```python
from scripts.fetcher import fetch_kline, calc_indicators
kline = fetch_kline("300042", "daily", 120)
indicators = calc_indicators(kline)
# 返回: ma5/10/20/60, RSI6/14, MACD+柱, KDJ, Bollinger, ICU均线(中泰2023), 鳄鱼线(招商2024), ADX, OBV
```

#### 东方财富资金流向（v2.2 新增）
```python
from scripts.fetcher import eastmoney_kline, eastmoney_sector_flow

# 个股基础数据（换手率、量比、市值）
data = eastmoney_kline("002842")

# 板块资金排行Top10
sectors = eastmoney_sector_flow(10)  # 主力净流入、涨跌幅、超大单、散户
```

### Layer 2: 分析层

#### 全市场扫描
```bash
python3 {baseDir}/scripts/analyzer.py scan
```
按板块输出涨跌幅排行（含多日趋势、假跌破检测）

#### 市场简报
```bash
python3 {baseDir}/scripts/analyzer.py report
```
生成Markdown格式日报，保存到 reports/ 目录

#### 市场状态检测
```bash
python3 {baseDir}/scripts/analyzer.py regime
```
判断当前市场处于牛市/熊市/震荡（均线偏离度法）

#### 板块资金流向采集
```python
from scripts.analyzer import collect_sector_flow
sf = collect_sector_flow(15)
```

### Layer 3: 决策层 — 多空辩论+风控审查

#### 完整五层辩论流程（TradingAgents架构）
```bash
python3 {baseDir}/scripts/debater.py 002842
```
输出：
- **多头论点**：均线、量能、RSI、MACD金叉、KDJ金叉、ICU均线、鳄鱼线、分歧转一致
- **空头论点**：超买、超涨、死叉、布林上轨、OBV流出
- **主持人裁决**：多/空/分歧
- **风控审查**：风险等级(高/中/低)、建议仓位上限、超买/波动率警报
- **分歧转一致信号**：缩量回调后放量突破、横盘启动、回踩支撑反弹

### Layer 4: 追踪层 — 推荐闭环（v2.2 新增）

#### 记录推荐
```bash
python3 {baseDir}/scripts/tracker.py record 002842 long 35.76 32.0 42.0 '钨涨价+分歧转一致'
```

#### 每日检查
```bash
python3 {baseDir}/scripts/tracker.py check
```
自动检查所有活跃推荐，含技术因子快照、止损/止盈触发、自动关闭

#### 生成报告
```bash
python3 {baseDir}/scripts/tracker.py report
```
输出Markdown格式追踪报告，显示每只推荐标的的入场价、当前收益、RSI/MACD/ICU状态

## 数据源

| 数据源 | 类型 | 数据内容 | 成本 |
|--------|------|---------|------|
| **新浪财经** (sina) | HTTP REST | 实时行情、日K/周K/分钟K线、板块涨跌排行

_meta.json

{
  "ownerId": "kn77debhbqfcs0ehymsrcx5mmd87wash",
  "slug": "finbot-stock",
  "version": "2.2.0",
  "publishedAt": 1781187026985
}

skill-card.md

## Description:

A股短线量化分析工具 — 实时行情、9因子选股、多空辩论+风控审查、推荐追踪闭环。数据源：新浪财经+东方财富（免费行情）。

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

## Publisher:

[zhubohan190601-crypto](https://clawhub.ai/user/zhubohan190601-crypto)

### License/Terms of Use:

MIT-0

## Use Case:

External users and developers use this skill to collect free A-share market data, calculate short-term technical factors, generate long/short debate analysis with risk review, and track recommendation outcomes. It supports market screening and reporting workflows, not investment advice.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Financial analysis can be incorrect or misleading, and the skill's own compliance statement says outputs are not investment advice.

Mitigation: Treat results as informational analysis only and require independent human review before any trading decision.

Risk: Some market data is fetched over unauthenticated HTTP or public finance endpoints, which can affect integrity and availability.

Mitigation: Cross-check important prices, flows, and indicators against trusted market data before acting on the output.

Risk: Recommendation, report, audit, and tracking files may persist strategy details locally.

Mitigation: Run the skill as an unprivileged user and keep generated local records in an access-controlled workspace.

Risk: Untrusted stock-code strings may be passed into command-line or data-fetching workflows.

Mitigation: Use known stock-code formats and avoid passing untrusted or unexpected strings to the scripts.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/zhubohan190601-crypto/skills/finbot-stock)
- [Sina Finance data source](https://finance.sina.com.cn)
- [Sina K-line API endpoint](https://quotes.sina.cn/cn/api/json_v2.php)
- [Eastmoney data source](http://data.eastmoney.com/)

## Skill Output:

**Output Type(s):** [text, markdown, code, shell commands, configuration, guidance]

**Output Format:** [Markdown reports, JSON-like Python dictionaries, shell commands, and Python import snippets]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [May write local reports, audit logs, and tracking records under the skill directory when its scripts are executed.]

## Skill Version(s):

2.2.0 (source: frontmatter and server release evidence)

## 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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