ClawHub

Quant Trading Assistant

v1.0.1

量化交易助手 - A股技术分析+量化选股。 用于：分析A股实时行情、计算技术指标（均线/KDJ/MACD/布林带）、 量化选股策略、生成交易信号、龙虎榜/情绪周期判断。 触发场景：问股票、分析行情、选股推荐、风险提示、技术指标计算。

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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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high confidence
✓
Purpose & Capability
The name/description (A股技术分析、量化选股) matches the code and SKILL.md: functions fetch quotes/K‑lines from Tencent/Sina, compute MA/KDJ/MACD/BOLL, provide screening and signal functions. There are no unrelated environment variables, binaries, or installs requested. Minor note: _meta.json/homepage exist but overall source provenance is limited (no authoritative upstream repo URL).
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Instruction Scope
SKILL.md explicitly documents the library functions and CLI commands and the code implements them. The runtime instructions do not direct the agent to read local files, secrets, or system config; they only call the included Python functions. The code performs outbound HTTP(S) calls to public finance APIs (expected for this purpose).
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Install Mechanism
There is no install spec — this is effectively instruction + a single Python file. No external archives or obscure download URLs are used. Risk from installation is low because nothing is written/installed by an installer spec.
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Credentials
The skill requires no credentials or environment variables. It makes network requests to public Tencent and Sina finance endpoints which is proportional to fetching market data. Note: those external services will see the stock symbols/queries you request — this is expected but is observable by the third parties.
✓
Persistence & Privilege
The skill is not always:true, does not request elevated/system privileges, and does not modify other skills or global agent configuration. It runs on demand and can be invoked by the agent normally.
Assessment
This skill appears to do what it claims: fetch public A‑share market data from Tencent/Sina and compute technical indicators. Before installing, consider: (1) outbound network calls — every symbol/query you ask the skill for is sent to third‑party finance APIs (Tencent/Sina), so treat queries as observable by those services; (2) provenance — the repository/source URL is not an authoritative upstream repo in the package metadata, so if you require strong supply‑chain assurance you may want to review the full source or prefer a vetted package; (3) accuracy — quant_screen uses a small hardcoded candidate list (not a live fundamental feed), so do not treat results as authoritative trading advice; (4) financial risk — the skill includes a disclaimer but any trading decisions remain your responsibility. If you need stronger guarantees, inspect the full Python file locally and run it in an isolated environment, or adapt data sources to your trusted feeds.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.
Termshttps://spdx.org/licenses/MIT-0.html

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