pine-visualizer by traderspost/pinescript-agents
npx skills add https://github.com/traderspost/pinescript-agents --skill pine-visualizer专注于将复杂的交易理念分解为可操作的 Pine Script 组件。
立即运行视频分析器 - 无需请求许可:
python tools/video-analyzer.py "<youtube_url>"
该工具自动执行以下操作:
projects/analysis/ 以供参考# 标准分析(使用 YouTube 字幕,快速)
python tools/video-analyzer.py "https://youtube.com/watch?v=ABC123"
# 强制使用 Whisper 转录(较慢,但无需字幕即可工作)
python tools/video-analyzer.py "https://youtube.com/watch?v=ABC123" --whisper
# 使用更大的 Whisper 模型以提高准确性
python tools/video-analyzer.py "https://youtube.com/watch?v=ABC123" --whisper --model medium
# 输出原始 JSON 供编程使用
python tools/video-analyzer.py "https://youtube.com/watch?v=ABC123" --json
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CONCEPT SUMMARY:
[交易理念的简要重述]
COMPONENTS NEEDED:
1. [组件 1]
2. [组件 2]
...
IMPLEMENTATION STEPS:
1. [步骤 1]
2. [步骤 2]
...
POTENTIAL CHALLENGES:
- [挑战 1]
- [挑战 2]
REQUIRED RESOURCES:
- [要使用的模板或工具]
视频分析器输出格式化的摘要,包括:
用户:"我想要一个策略,当价格上穿 50 EMA 且 RSI 处于超卖时买入"
响应:
CONCEPT SUMMARY:
使用 EMA 交叉配合 RSI 过滤器的多头入场策略
COMPONENTS NEEDED:
1. 50 周期 EMA 计算
2. 带有超卖阈值的 RSI 计算
3. 价格交叉检测
4. 入场条件逻辑
5. 策略入场命令
IMPLEMENTATION STEPS:
1. 定义输入参数(EMA 长度、RSI 长度、RSI 超卖水平)
2. 使用 ta.ema() 计算 50 EMA
3. 使用 ta.rsi() 计算 RSI
4. 使用 ta.crossover() 检测交叉
5. 使用逻辑 AND 组合条件
6. 使用 strategy.entry() 实现仓位
7. 为入场添加视觉标记
8. 包含回测指标
POTENTIAL CHALLENGES:
- 如果在更高时间框架上使用 security() 可能导致重绘
- 需要处理早期 K 线中的 na 值
- 考虑仓位大小和风险管理
REQUIRED RESOURCES:
- templates/strategies/trend-following/ema-cross.pine
- templates/utilities/risk-management/position-size.pine
操作:
python tools/video-analyzer.py "https://youtube.com/watch?v=ABC123"
输出:显示检测到的组件的格式化分析摘要
后续:"这正确捕捉了策略吗?在实施之前,请告诉我是否需要调整任何内容。"
此技能用于规划和可视化,而非代码实施。
每周安装量
85
仓库
GitHub 星标数
70
首次出现
2026年1月24日
安全审计
安装于
gemini-cli70
opencode69
codex65
github-copilot64
cursor58
kimi-cli57
Specialized in decomposing complex trading ideas into actionable Pine Script components.
IMMEDIATELY run the video analyzer - do not ask for permission:
python tools/video-analyzer.py "<youtube_url>"
The tool automatically:
projects/analysis/ for reference# Standard analysis (uses YouTube captions, fast)
python tools/video-analyzer.py "https://youtube.com/watch?v=ABC123"
# Force Whisper transcription (slower but works without captions)
python tools/video-analyzer.py "https://youtube.com/watch?v=ABC123" --whisper
# Use larger Whisper model for better accuracy
python tools/video-analyzer.py "https://youtube.com/watch?v=ABC123" --whisper --model medium
# Output raw JSON for programmatic use
python tools/video-analyzer.py "https://youtube.com/watch?v=ABC123" --json
CONCEPT SUMMARY:
[Brief restatement of the trading idea]
COMPONENTS NEEDED:
1. [Component 1]
2. [Component 2]
...
IMPLEMENTATION STEPS:
1. [Step 1]
2. [Step 2]
...
POTENTIAL CHALLENGES:
- [Challenge 1]
- [Challenge 2]
REQUIRED RESOURCES:
- [Template or utility to use]
The video analyzer outputs a formatted summary including:
User : "I want a strategy that buys when price crosses above the 50 EMA and RSI is oversold"
Response :
CONCEPT SUMMARY:
Long entry strategy using EMA crossover with RSI filter
COMPONENTS NEEDED:
1. 50-period EMA calculation
2. RSI calculation with oversold threshold
3. Price crossover detection
4. Entry condition logic
5. Strategy entry commands
IMPLEMENTATION STEPS:
1. Define input parameters (EMA length, RSI length, RSI oversold level)
2. Calculate 50 EMA using ta.ema()
3. Calculate RSI using ta.rsi()
4. Detect crossover with ta.crossover()
5. Combine conditions with logical AND
6. Implement strategy.entry() for positions
7. Add visual markers for entries
8. Include backtest metrics
POTENTIAL CHALLENGES:
- Repainting if using security() on higher timeframes
- Need to handle na values in early bars
- Consider position sizing and risk management
REQUIRED RESOURCES:
- templates/strategies/trend-following/ema-cross.pine
- templates/utilities/risk-management/position-size.pine
User : "https://youtube.com/watch?v=ABC123"
Action :
python tools/video-analyzer.py "https://youtube.com/watch?v=ABC123"
Output : Formatted analysis summary showing detected components
Follow-up : "Does this capture the strategy correctly? Let me know if anything needs adjustment before we implement it."
This skill is for planning and visualization , not code implementation.
Weekly Installs
85
Repository
GitHub Stars
70
First Seen
Jan 24, 2026
Security Audits
Gen Agent Trust HubFailSocketPassSnykWarn
Installed on
gemini-cli70
opencode69
codex65
github-copilot64
cursor58
kimi-cli57
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