Agent skill · Data & Analytics

longbridge-quant

Server-side quantitative indicator runner via Longbridge Securities — execute Pine Script v6 syntax subset against historical K-line data on Longbridge servers without a local Python environment. Supports built-in indicators (MACD, RSI, Bollinger Bands, EMA, SMA, etc.) and custom calculation logic; results returned as JSON. Triggers: "量化指标", "Pine Script", "指标计算", "MACD计算", "RSI计算", "服务端指标", "指标脚本", "量化脚本", "技术指标运行", "量化指標", "指標計算", "MACD計算", "RSI計算", "服務端指標", "指標腳本", "quant indicator", "Pine Script", "indicator calculation", "run indicator", "server-side quant", "MACD script", "RSI calculatio

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill longbridge-quant --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 5 KB
Bundled scripts: none
Version: 1.0.0
Declared author: longbridge
Path: skills/analysis/longbridge-quant/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# longbridge-quant Server-side quantitative indicator runner: execute Pine Script v6 syntax subset on historical K-line data via Longbridge Securities servers. > ⚠️ **Beta feature**: `longbridge quant run` may return `internal server error` if the feature is not yet enabled for your account. Contact Longbridge support to enable quantitative script access if needed. > **Response language**: match the user's input language — Simplified Chinese / Traditional Chinese / English. ## When to use - *"帮我算 TSLA 的 MACD"*, *"計算 RSI(14)"*, *"run MACD on NVDA"* → `longbridge quant run` with a built-in `ta.*` function - *"用 Pine Script 算布林带"*, *"自定义指标脚本"*, *"custom Pine Script indicator"* → pass a script string or pipe a `.pine` file - *"我想看近一年 EMA20"*, *"EMA 20 for the past year"* → set `--start` / `--end` accordingly For raw OHLCV data without indicator logic, defer to `longbridge-kline`. For visual chart output, defer to `longbridge-kline`. ## Workflow 1. Identify the symbol, date range, and indicator expression from the prompt. 2. Run `longbridge quant run --help` to check supported functions and flags before constructing the call. 3. Build the `--script` string using Pine Script v6 `ta.*` bu

What's inside
Steps it walks through
  1. When to use
  2. Workflow
  3. CLI
  4. Output
  5. Error handling
  6. MCP fallback
  7. Related skills
  8. File layout
Ships with 1 file
  • metadata.json
Commands it runs
Inspect supported functions and flags first
longbridge quant run --help
Single built-in indicator — 20-day EMA
longbridge quant run AAPL.US --start 2025-01-01 --end 2025-12-31 \
longbridge quant run TSLA.US --start 2026-01-01 --end 2026-04-30 \
longbridge quant run NVDA.US --start 2025-01-01 --end 2026-01-01 \
Bollinger Bands
longbridge quant run 700.HK --start 2025-06-01 --end 2025-12-31 \
Pipe a custom Pine Script file
cat myindicator.pine | longbridge quant run AAPL.US \
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About this skill
What does the longbridge-quant skill do?

Server-side quantitative indicator runner via Longbridge Securities — execute Pine Script v6 syntax subset against historical K-line data on Longbridge servers without a local Python environment. Supports built-in indicators (MACD, RSI, Bollinger Bands, EMA, SMA, etc.) and custom calculation logic; results returned as JSON. Triggers: "量化指标", "Pine Script", "指标计算", "MACD计算", "RSI计算", "服务端指标", "指标脚本", "量化脚本", "技术指标运行", "量化指標", "指標計算", "MACD計算", "RSI計算", "服務端指標", "指標腳本", "quant indicator", "Pine Script", "indicator calculation", "run indicator", "server-side quant", "MACD script", "RSI calculatio

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill longbridge-quant --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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