Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Data Analysis
Claw Screener
Stock screener combining Williams %R oversold signals with Warren Buffett-style fundamental analysis. Supports US (S&P 500) and Thai (SET) markets.
skill openclawclawhub Free
Stock screener combining Williams %R oversold signals with Warren Buffett-style fundamental analysis. Supports US (S&P 500) and Thai (SET) markets.
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md, package-lock.json, package.json, scripts/set.txt, src/analyze.ts
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.3
Provenance
- Publisher
- rsoutar
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Claw-Screener
A stock screener that combines technical analysis (Williams %R oversold signals) with Warren Buffett-style fundamental analysis using SEC data. Supports US (S&P 500) and Thai (SET) markets.
When to Use This Skill
Use this skill when you need to: Find oversold stocks with strong fundamentals Screen for quality stocks using Buffett's 10 formulas Screen for long-term compounders using Carlson filters (ROIC, growth, buybacks) Analyze individual stocks for investment decisions Get daily stock screening results in text, JSON, or Telegram format
Tools
This skill provides the following capabilities:
1. Combined Screening
Finds stocks that are both technically oversold (Williams %R < -80) and fundamentally strong (Buffett score >= threshold). Command: bun run src/screening.ts [options] Options: FlagDescriptionDefault--marketMarket: us or bkus--min-scoreMinimum Buffett score (0-10)5--top-nNumber of results to show10--formatOutput: text, json, telegramtext Examples: bun run src/screening.ts bun run src/screening.ts --market us --min-score 7 --top-n 5 bun run src/screening.ts --market bk bun run src/screening.ts --format json bun run src/screening.ts --format telegram
2. Technical Only Scan
Fast oversold scan using Williams %R indicator only. No SEC data required. Works for both US and Thai markets. Command: bun run src/technicalOnly.ts [options] Options: FlagDescriptionDefault--marketMarket: us or bkus--thresholdWilliams %R threshold-80--top-nNumber of results to show20--formatOutput: text, json, telegramtext Examples: bun run src/technicalOnly.ts bun run src/technicalOnly.ts --threshold -70 --top-n 50 bun run src/technicalOnly.ts --market bk
3. Analyze Stock
Deep analysis of a single stock using Buffett's 10 formulas. Command: bun run src/analyze.ts <ticker> [options] Options: FlagDescriptionDefault--formatOutput: text, json, telegramtext Examples: bun run src/analyze.ts AAPL bun run src/analyze.ts MSFT --format telegram bun run src/analyze.ts GOOGL --format json bun run src/analyze.ts PTT.BK
4. Compounding Machine
Screens for "compounders" using Carlson-style filters: Revenue and net income YoY trend strength ROIC threshold (default >15%) Share count reduction over 3 years (buyback signal) Operating margin threshold (default >20%) Includes current yield vs 5-year average and a simple 10-year DCF context Command: bun run src/compoundingMachine.ts [options] Options: FlagDescriptionDefault--marketMarket universe: us or bkus--tickersComma-separated tickers (overrides market universe)---max-tickersLimit universe sizeall--top-nNumber of passing stocks to show25--concurrencyParallel fetch workers4--formatOutput: text or jsontext--db-pathSQLite cache pathsec_cache.db--ttl-daysCache TTL in days7--min-roicROIC threshold (%)15--min-op-marginOperating margin threshold (%)20--min-buybackRequired 3Y share reduction (%)2--show-rejectedInclude failed tickers with reasons in outputoff Examples: bun run src/compoundingMachine.ts bun run src/compoundingMachine.ts --tickers AAPL,MSFT,NVDA --top-n 10 bun run src/compoundingMachine.ts --format json --max-tickers 100 bun run src/compoundingMachine.ts --tickers PLTR --show-rejected Runtime / Caching Notes: First uncached run on full US universe can take ~20-30+ minutes. This is expected: each ticker requires multiple Yahoo fundamentals/quote requests and retry backoff for rate-limit resilience. Subsequent runs are much faster due to SQLite caching (sec_cache.db, TTL default 7 days). For quick checks, run smaller scans first (for example --max-tickers 50 or specific --tickers). Agent Guidance for User Messaging: If user runs full-universe Compounding Machine scan, explicitly warn that initial run may take ~20-30 minutes. Suggest quick-test alternatives while waiting: bun run src/compoundingMachine.ts --max-tickers 50 bun run src/compoundingMachine.ts --tickers AAPL,MSFT,NVDA
5. Watchlist Management
Track stocks you're interested in and get alerts when they become oversold or overbought. Command: bun run src/watchList.ts <command> [options] Commands: CommandDescriptionadd <ticker>Add a stock to your watchlistremove <ticker>Remove a stock from your watchlistlistShow all watched stocks Options: FlagDescriptionDefault--market us|thMarket: us (US) or th (Thai)us--notes '...'Optional notes for the stock---alert-thresholdWilliams %R threshold for alerts- Examples: bun run src/watchList.ts add AAPL bun run src/watchList.ts add AAPL --market us --notes 'Big tech' bun run src/watchList.ts add PTT.BK --market th bun run src/watchList.ts remove AAPL bun run src/watchList.ts list bun run src/watchList.ts list --market us Storage: Watchlist is saved to ~/.claw-screener-watchlist.json
Buffett's 10 Formulas
The fundamental analysis evaluates stocks against Warren Buffett's criteria: #FormulaTargetDescription1Cash Test> Total DebtCash covers all debt2Debt-to-Equity< 0.5Low leverage3Return on Equity> 15%Efficient use of capital4Current Ratio> 1.5Short-term liquidity5Operating Margin> 12%Operational efficiency6Asset Turnover> 0.5Asset efficiency7Interest Coverage> 3xAbility to pay interest8Earnings StabilityPositiveConsistent profitability9Free Cash Flow> 0Cash generation10Capital Allocation> 15% ROEManagement effectiveness Scoring: Each passing formula earns 1 point. Maximum score: 10/10.
Technical Indicator
Williams %R (Williams Percent Range) Range: -100 to 0 Oversold: < -80 (potential buy signal) Overbought: > -20 (potential sell signal)
Combined Score Formula
Combined score = (Technical Score × 0.3) + (Fundamental Score × 0.7) Technical Score: (Williams %R + 100) / 100 Fundamental Score: (Buffett Score / 10) × 100
Data Sources
US Stocks: SEC EDGAR for fundamentals, Yahoo Finance for prices Thai Stocks: Yahoo Finance only (no SEC data available)
Runtime Requirements
Bun (>=1.3.1) - Required runtime for executing TypeScript scripts Node.js is NOT required as Bun provides all necessary runtime functionality
Install Bun
If you don't have Bun installed, run: # macOS/Linux curl -fsSL https://bun.sh/install | bash # Windows (PowerShell) iwr https://bun.sh/install -outfile "install.ps1"; ./install.ps1
Install Dependencies
bun install
File Persistence
This skill creates and manages the following files: FileLocationPurposeTTLWatchlist~/.claw-screener-watchlist.jsonUser's stock watchlistPermanentSEC Cachesec_cache.dbCached SEC EDGAR financial data7 days (default)Price Cacheprice_cache.dbCached stock price data1 day (default)
Cache Management
Cache files are automatically created on first run Use --ttl-days flag with compounding machine to adjust cache TTL Cache files can be deleted to force fresh data fetch Cache improves performance significantly on subsequent runs
Notes
First run on full US universe can take ~20-30+ minutes (expected behavior) Subsequent runs are much faster due to caching For quick tests, use --max-tickers 50 or specific --tickers
Bun Scripts
bun run dev # Run screening (alias for bun run src/screening.ts) bun run screening # Run combined screening bun run technical # Run technical-only scan bun run analyze # Analyze a stock (requires ticker argument) bun run compounder # Run Compounding Machine screener bun run watchlist:add # Add stock to watchlist bun run watchlist:remove # Remove stock from watchlist bun run watchlist:list # List watched stocks
Text (Default)
📊 Combined Quality Screening (US (S&P 500)) Technical: Oversold signals (Williams %R < -80) Fundamental: Warren Buffett's 10 formulas on SEC data Minimum Buffett Score: 5/10 Results: Total Scanned: 503 Oversold Found: 42 Quality Stocks: 8 (Buffett ≥5/10) Top 10 Opportunities: 1. AAPL — Combined: 85.2% | Buffett: 8/10 | WR: -82.3 2. MSFT — Combined: 79.1% | Buffett: 7/10 | WR: -85.1
Telegram
📊 Combined Quality Screening (US (S&P 500)) Scanned: 503 stocks Oversold: 42 Quality (Buffett ≥5/10): 8 🌟 Top 10 Quality Opportunities: 1. **AAPL** — Combined: 85% | Buffett: 8/10 | WR: -82.3 2. **MSFT** — Combined: 79% | Buffett: 7/10 | WR: -85.1
Category context
Data access, storage, extraction, analysis, reporting, and insight generation.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs2 Config1 Scripts1 Files
- SKILL.md
- README.md
- src/analyze.ts
- package-lock.json
- package.json
- scripts/set.txt