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Claude Skills by tools-only
github.com/tools-only19,166 skills18 installs6,168 views
- 2480 Fmp Api Guide C39b1f5eFinancial Modeling Prep provides comprehensive financial data APIs for stocks, forex, cryptocurrencies, and more. This guide focuses on endpoints used for dividend stock screening.Votes: 0GitHub stars: 9
- 2481 Plugin Quick Start Db0b7f1c``` plugins/my_plugin/ ├── __init__.py # from .plugin import MyPlugin ├── plugin.py # 插件主类，定义数据爬取的格式转换，入库前的校验和存储逻辑 ├── extractor.py # 数据爬取逻辑 ├── config.json # 插件配置，包括调用的接口名称，调度频率等 ├── schema.json # clickhouse表结构定义 ├── service.py # 数据查询的sdk， services/目录下的http_server与mcp_server会基于此文件生成对应的查询接口 └── README.md # 插件文档 ```Votes: 0GitHub stars: 9
- 2481 Readme Hk Daily 5ddf8c7fThis script fetches historical daily data for all HK stocks from Finnhub API and stores them in the ClickHouse database.Votes: 0GitHub stars: 9
- 2481 Rsi Oversold Strategy 34906933The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and magnitude of recent price changes to evaluate overbought or oversold conditions.Votes: 0GitHub stars: 9
- 2481 Transient Sauteeing Raven C6d096a4The current `chat` command uses a keyword-based REPL (`TradingOrchestrator` + `InteractiveSession`) that counts keyword matches to route queries. It has no LLM reasoning, no conversation memory between queries, and can't handle ambiguous questions.Votes: 0GitHub stars: 9
- 2482 Ai Stock Platform Design 77dcc7a7> 版本: 1.2.0 > 日期: 2026-01-09 > 状态: 设计阶段 > 更新: 新增 M05 用户记忆、M06 数据管理、M07 持仓管理、M08 策略回测模块 ---Votes: 0GitHub stars: 9
- 2482 Design F5d51142港股日线数据是股票分析的重要基础数据。当前系统使用 TuShare API 获取港股日线数据,但由于权限限制,无法获取完整的历史数据。需要迁移到数据完整且稳定的数据源。Votes: 0GitHub stars: 9
- 2482 Ftd Methodology Ad12220eThe Follow-Through Day (FTD) is William O'Neil's market timing signal for confirming a new uptrend after a correction. It is the **single most important signal** for re-entering the market after a decline. Without an FTD, no new bull market or sustained rally has ever begun (per IBD historical analysis).Votes: 0GitHub stars: 9
- 2483 13f Filings Guide 3856a861Form 13F is a quarterly report filed with the SEC by institutional investment managers with at least $100 million in assets under management (AUM). The form discloses their equity holdings as of the end of each calendar quarter.Votes: 0GitHub stars: 9
- 2483 Cli Guide 07b09d25本文档介绍 A股赛博操盘手 的命令行工具使用方法。Votes: 0GitHub stars: 9
- 2484 Database Setup 419ba41a本文档介绍如何为 A股赛博操盘手 系统设置数据库。Votes: 0GitHub stars: 9
- 2484 Institutional Investor Types 65d016c6Not all institutional investors are created equal. Understanding the different types of institutions, their investment strategies, time horizons, and motivations is critical for interpreting 13F filing changes. This guide categorizes institutional investors and explains how to weight their buy/sell signals.Votes: 0GitHub stars: 9
- 2484 Risk Management Framework 326fdcf2This framework provides senior project managers with quantitative risk analysis methodologies, decision frameworks, and portfolio-level risk management strategies. It goes beyond basic risk identification to provide sophisticated tools for risk quantification, Monte Carlo simulation, expected monetary value (EMV) analysis, and enterprise risk appetite frameworks.Votes: 0GitHub stars: 9
- 2485 Interpretation Framework 17277b19This framework provides a systematic approach to interpreting institutional ownership changes and converting 13F filing data into actionable investment signals. Use this as a decision tree for analyzing stocks discovered through institutional flow tracking.Votes: 0GitHub stars: 9
- 2485 Ods Stock Basic 7ecb27d3基于对 **fin-agent** 项目优秀实践的深入学习，成功实现了完整的持仓管理功能，充分利用 **ClickHouse** 数据库的高性能特性，构建了一个现代化的智能投资组合管理系统。Votes: 0GitHub stars: 9
- 2486 Historical Regimes 2ae21390Reference cases for the 5 regime classifications. Use these to contextualize current readings and identify historical parallels.Votes: 0GitHub stars: 9
- 2487 Indicator Interpretation Guide Bbf0e06fQuick reference for interpreting each component's output values and signals.Votes: 0GitHub stars: 9
- 2488 Regime Detection Methodology C8fa6cc4The Macro Regime Detector uses a 3-layer signal detection approach applied to 6 cross-asset ratios, analyzed at monthly frequency with 6-month and 12-month Simple Moving Averages.Votes: 0GitHub stars: 9
- 2489 Breadth Analysis Methodology 48a3b229Market breadth measures the degree of participation in a market move. A healthy advance is characterized by broad participation (many stocks rising), while a narrowing market (fewer stocks leading) often precedes corrections.Votes: 0GitHub stars: 9
- 2490 Analysis Patterns 30c850381. **Uptrend** - Higher highs and higher lows - Moving averages trending upward - Price rises accompanied by volume increasesVotes: 0GitHub stars: 9
- 2491 Indicators Edf91528- **Nikkei 225**: Stock price average of 225 representative stocks on Tokyo Stock Exchange Prime - Key levels: 30,000, 35,000, 40,000 yen - Moving averages: Emphasize 25-day, 75-day, 200-day linesVotes: 0GitHub stars: 9
- 2492 Corporate News Impact E2d0c372**"Magnificent 7" Era (2023-2024):** - Apple, Microsoft, NVIDIA, Amazon, Google, Meta, Tesla - Combined: ~25-30% of S&P 500 market cap - Index-level impact from individual company movesVotes: 0GitHub stars: 9
- 2493 Geopolitical Commodity Correlations B404fb71**Middle East Conflicts:**Votes: 0GitHub stars: 9
- 2494 Market Event Patterns 9b835e76**Event Types:** - Federal Funds Rate Decisions - Quantitative Easing (QE) / Quantitative Tightening (QT) Announcements - Forward Guidance Changes - Emergency Policy ActionsVotes: 0GitHub stars: 9
- 2495 Trusted News Sources 49e1cc93**Federal Reserve:** - FederalReserve.gov - FOMC statements, meeting minutes, economic projections - Federal Reserve Economic Data (FRED) - St. Louis Fed database - Fed Chair speeches and testimoniesVotes: 0GitHub stars: 9
- 2496 Market Top Methodology 059a1da0This framework integrates three proven approaches to market top detection, each targeting different aspects of institutional behavior that precede significant market declines (10-20% corrections).Votes: 0GitHub stars: 9
- 2497 Cointegration Guide Ec27ea671. [What is Cointegration?](#what-is-cointegration) 2. [Cointegration vs Correlation](#cointegration-vs-correlation) 3. [Augmented Dickey-Fuller (ADF) Test](#augmented-dickey-fuller-adf-test) 4. [Practical Implementation](#practical-implementation) 5. [Interpreting Results](#interpreting-results) 6. [Half-Life Estimation](#half-life-estimation) 7. [Testing for Structural Breaks](#testing-for-structural-breaks) 8. [Case Studies](#case-studies)Votes: 0GitHub stars: 9
- 2498 Alpaca Mcp Setup Fdfb5774This guide explains how to set up and configure the Alpaca MCP (Model Context Protocol) Server for use with the Portfolio Manager skill.Votes: 0GitHub stars: 9
- 2499 Asset Allocation Afb273dbThis document provides comprehensive guidance on asset allocation principles, target allocations by risk profile, and rebalancing triggers for portfolio management.Votes: 0GitHub stars: 9
- 2500 Diversification Principles 246880e1This document explains the theory and practice of portfolio diversification, providing frameworks for assessing diversification quality and identifying concentration risks.Votes: 0GitHub stars: 9
- 2501 Portfolio Risk Metrics Aeec1fb1This document provides comprehensive guidance on measuring and interpreting portfolio risk using standard financial metrics.Votes: 0GitHub stars: 9
- 2502 Position Evaluation 274428e8This document provides a systematic framework for evaluating individual positions within a portfolio to determine appropriate actions: HOLD, ADD, TRIM, or SELL.Votes: 0GitHub stars: 9
- 2503 Rebalancing Strategies 9adf61ffThis document provides comprehensive guidance on portfolio rebalancing methodologies, timing strategies, tax optimization, and implementation best practices.Votes: 0GitHub stars: 9
- 2504 Risk Profile Questionnaire 2043a448This document provides a framework for assessing investor risk tolerance and determining appropriate target asset allocation.Votes: 0GitHub stars: 9
- 2505 Target Allocations C3896338This document provides model portfolio allocations for different investor risk profiles, serving as benchmarks for portfolio analysis and rebalancing.Votes: 0GitHub stars: 9
- 2506 Sector Rotation 9179d38cThe economic cycle can be divided into four primary phases, each characterized by distinct economic conditions and sector performance patterns.Votes: 0GitHub stars: 9
- 2507 Cross Sector Themes B5fd9503This reference defines market themes by their constituent FINVIZ industries, sectors, proxy ETFs, and representative stocks. The theme_classifier.py script reads these definitions to map industry-level data into theme-level aggregations. **Usage Notes:** - Industry names must exactly match FINVIZ industry names (see `finviz_industry_codes.md`) - `min_matching_industries`: Minimum number of constituent industries that must show activity for the theme to be detected - `static_stocks`: Fallback ...Votes: 0GitHub stars: 9
- 2508 Finviz Industry Codes 174a753eThis reference maps all FINVIZ industry names to their corresponding filter codes used in the FINVIZ Screener API and Elite CSV export URLs. **URL Pattern (Elite CSV Export):** ``` https://elite.finviz.com/export.ashx?v=151&f=ind_{code},cap_smallover&auth={API_KEY} ``` **URL Pattern (Public Screener):** ``` https://finviz.com/screener.ashx?v=151&f=ind_{code},cap_smallover ``` **Filter Code Convention:** `ind_` + lowercase industry name with spaces, hyphens, ampersands, and special characters ...Votes: 0GitHub stars: 9
- 2509 Thematic Etf Catalog 684d4dd4This catalog maps market themes to their associated ETFs. The ETF count per theme is used for the `etf_proliferation_score` in lifecycle maturity assessment. **ETF Proliferation Scoring:** | ETF Count | Score | |-----------|-------| | 0 | 0 | | 1 | 20 | | 2-3 | 40 | | 4-6 | 60 | | 7-10 | 80 | | >10 | 100 | Higher ETF proliferation indicates more retail/institutional interest and a potentially more mature (crowded) theme. ---Votes: 0GitHub stars: 9
- 2510 Theme Detection Methodology C7d058dcThe Theme Detector uses a **3-Dimensional Scoring Model** to identify, rank, and assess market themes. Unlike single-score ranking systems, this approach separates the intensity of a theme (heat), its maturity stage (lifecycle), and the reliability of the signal (confidence) into independent dimensions.Votes: 0GitHub stars: 9
- 2511 Uptrend Methodology Cf2359f3Monty's Uptrend Ratio Dashboard tracks approximately 2,800 US stocks across 11 GICS sectors. For each stock, it determines whether the stock is in an "uptrend" based on the criteria below. The dashboard publishes daily CSV data on GitHub.Votes: 0GitHub stars: 9
- 2512 Bubble Framework 50d566aa1. [Core Concept](#core-concept) 2. [Minsky/Kindleberger Model](#minskykindleberger-model) 3. [Behavioral Psychology Elements](#behavioral-psychology-elements) 4. [Quantitative Indicators for Detection](#quantitative-indicators-for-detection) 5. [Practical Response Strategies](#practical-response-strategies)Votes: 0GitHub stars: 9
- 2512 Skill World 51308621International legal notice requirements. UK, Switzerland, USA, and worldwide best practices for multi-jurisdiction websites.Votes: 0GitHub stars: 9
- 2513 Cookies 0bc33171> Référence : Lignes directrices CNIL (2020) + Directive ePrivacy > > **Documentation** : [CNIL_transparence.pdf](assets/CNIL_transparence.pdf)Votes: 0GitHub stars: 9
- 2513 Cookies D743e386> Référence : Lignes directrices CNIL (2020) + Directive ePrivacy > **Documentation** : [CNIL_transparence.pdf](assets/CNIL_transparence.pdf)Votes: 0GitHub stars: 9
- 2513 Quick Reference En Bdd813ca``` □ Step 1: Update Bubble-O-Meter (2 min) - Score 8 indicators (0-2 points each) - Check risk budget based on total scoreVotes: 0GitHub stars: 9
- 2513 Skill Psychology 84cacb4270+ marketing mental models and psychological principles for persuasion and conversion.Votes: 0GitHub stars: 9
- 2514 Financial Metrics 8324f69a**Gross Profit Margin** - Formula: (Revenue - COGS) / Revenue × 100 - Measures: Production efficiency and pricing power - Higher is better; compare to industry averageVotes: 0GitHub stars: 9
- 2515 Screening Methodology C723c1deThis screening methodology identifies high-quality dividend stocks that combine: - **Value characteristics**: Reasonable valuations (low P/E, P/B) - **Income generation**: Attractive dividend yields (>=3.5%) - **Growth profile**: Consistent dividend, revenue, and EPS growth - **Quality metrics**: Strong profitability, financial health, and dividend sustainabilityVotes: 0GitHub stars: 9
- 2516 Scoring System 8a4825b6| Component | Weight | Source | |-----------|--------|--------| | Trend Template (Stage 2) | 25% | 7-point Minervini criteria | | Contraction Quality | 25% | VCP pattern detection | | Volume Pattern | 20% | Volume dry-up analysis | | Pivot Proximity | 15% | Distance from breakout level | | Relative Strength | 15% | Minervini-weighted RS vs S&P 500 |Votes: 0GitHub stars: 9