Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Data Analysis
trading212 Skill
Analyzes Trading212 portfolio, generates daily summaries with P&L and top gainers/losers, makes trade proposals based on configurable rules, and can place or...
skill openclawclawhub Free
Analyzes Trading212 portfolio, generates daily summaries with P&L and top gainers/losers, makes trade proposals based on configurable rules, and can place or...
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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
- reference.md, requirements.txt, SKILL.md, scripts/proposal_rules.py, scripts/t212_client.py, scripts/cache.py
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
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- 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. Tell me what you changed and call out any manual steps you could not complete.
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- nandichi
- Source page
- View original listing
- Canonical URL
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Documentation
Trading212 Skill
Connects to the Trading212 API to provide portfolio analysis, trade proposals, and order execution. Important: By default all operations run against the demo (paper-trading) environment. Set TRADING212_DEMO=false only when you are absolutely sure the user wants to trade with real money.
Prerequisites
Install dependencies once from the skill's script directory: pip install -r {baseDir}/requirements.txt
1. summary -- Daily portfolio overview
python3 {baseDir}/scripts/trading212_skill.py --mode summary Returns structured JSON with: Total portfolio value, cash, daily change (EUR + %) Per-position details (quantity, avg price, current price, unrealised P&L) Top gainers and top losers Notable events (orders filled today, dividends received) Multi-period performance (1 week, 1 month, 3 months, 1 year) Use this when the user asks: "How did my portfolio do today?", "Give me a summary", "What happened in my portfolio?" Present the JSON output as a readable English summary. Highlight the daily change prominently, list top gainers and losers, and mention notable events.
2. propose -- Trade proposals
python3 {baseDir}/scripts/trading212_skill.py --mode propose python3 {baseDir}/scripts/trading212_skill.py --mode propose --risk low python3 {baseDir}/scripts/trading212_skill.py --mode propose --risk high Returns a list of suggested actions (buy, sell, reduce, hold) with quantities and reasons. Rules are configured in config/rules.yaml. Active rules: Reduce on drop: Propose reducing positions that dropped significantly today with large weight Take profit: Propose selling small positions with high unrealised gain DCA buy: Propose buying tickers on the DCA list when enough cash is available Stop-loss: Propose selling when price drops below stop-loss threshold vs average purchase price Max exposure: Propose reducing when a single position exceeds maximum portfolio weight Cost averaging: Propose buying more when price is significantly below average purchase price Cash reserve: Warn when cash falls below minimum percentage of portfolio Use this when the user asks: "What should I do?", "Any trade suggestions?", "Should I buy or sell anything?" Present proposals clearly. Always ask the user for confirmation before executing any proposed trade. Never execute trades automatically.
3. execute_trade -- Place an order
python3 {baseDir}/scripts/trading212_skill.py --mode execute_trade --params '{"symbol":"AAPL_US_EQ","side":"buy","quantity":5,"order_type":"market"}' Parameters (JSON): symbol (required): Trading212 ticker, e.g. "AAPL_US_EQ" side (required): "buy" or "sell" quantity (required): positive number of shares order_type: "market" (default) or "limit" limit_price: required when order_type is "limit" Pre-trade validation is performed automatically: Buy orders: checks if enough cash is available Sell orders: checks if enough shares are held CRITICAL SAFETY RULES: NEVER execute a trade without explicit user confirmation. Always show the user exactly what will be executed (symbol, side, quantity, order type) and ask "Shall I place this order?" before running. If TRADING212_DEMO=true (the default), remind the user this is a paper-trade. If TRADING212_DEMO=false, warn the user clearly that this is a REAL order with real money.
4. dividends -- Dividend overview
python3 {baseDir}/scripts/trading212_skill.py --mode dividends Returns structured JSON with: Total dividends received (all time and last 12 months) Per-ticker breakdown with totals, last payment date, and estimated annual yield Dividend calendar (most recent payment per ticker) Use this when the user asks: "How much dividend did I receive?", "What are my dividends?", "When was my last dividend?"
5. history -- Order history
python3 {baseDir}/scripts/trading212_skill.py --mode history python3 {baseDir}/scripts/trading212_skill.py --mode history --params '{"ticker":"AAPL_US_EQ","days":30}' Returns structured JSON with: Total number of historical orders Realized P&L per ticker and overall Full order list with dates, prices, and quantities Optional parameters (JSON): ticker: Filter by specific ticker days: Limit to orders from the last N days Use this when the user asks: "Show my order history", "How much profit did I realize?", "What did I trade last month?"
6. watchlist -- Price monitoring
python3 {baseDir}/scripts/trading212_skill.py --mode watchlist Reads config/watchlist.yaml and checks price alerts for each ticker. Returns: List of watchlist items with current prices (if held) Triggered alerts (price above or below configured thresholds) Configure the watchlist in config/watchlist.yaml: watchlist: - ticker: "NVDA_US_EQ" alert_below: 100.0 alert_above: 150.0 Use this when the user asks: "Check my watchlist", "Any price alerts?", "What are my watched stocks doing?"
7. allocation -- Portfolio allocation analysis
python3 {baseDir}/scripts/trading212_skill.py --mode allocation python3 {baseDir}/scripts/trading212_skill.py --mode allocation --rebalance Returns structured JSON with: Current weight per position vs target allocation Deviation from target per position Missing target tickers (in target but not held) Cash allocation vs target With --rebalance flag, also generates buy/sell proposals to move toward target allocation. Configure target allocation in config/allocation.yaml: target_allocation: "VWCE.UK": 40.0 "IWDA.UK": 30.0 _cash: 5.0 Use this when the user asks: "How is my portfolio allocated?", "Am I balanced?", "What should I rebalance?"
Output Format
All modes return structured JSON to stdout. Parse it and present a human-readable English summary to the user.
Additional Resources
For full output schemas and API details, see reference.md.
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
3 Scripts2 Docs1 Files
- SKILL.md
- reference.md
- scripts/cache.py
- scripts/proposal_rules.py
- scripts/t212_client.py
- requirements.txt