Trading Signal Analysis: Ingest OHLCV datasets for any stock or cryptocurrency and generate. Use when an agent needs trading signal analysis, generate buy and sell trading signals from technical indicators, backtest trading strategies against historical ohlcv price data, analyze maximum adverse excursion and maximum favorable excursion for trade risk, calculate win rate and expectancy for systematic trading strategies, analyze signals, candles, symbol through AgentPMT-hosted remote tool calls.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Une commande directe contourne le prompt de vérification. Examinez la source avant de l'exécuter.
Trading Signal Analysis: Ingest OHLCV datasets for any stock or cryptocurrency and generate. Use when an agent needs trading signal analysis, generate buy and sell trading signals from technical indicators, backtest trading strategies against historical ohlcv price data, analyze maximum adverse excursion and maximum favorable excursion for trade risk, calculate win rate and expectancy for systematic trading strategies, analyze signals, candles, symbol through AgentPMT-hosted remote tool calls.
Agent instructions for AgentPMT-hosted remote tool calls. Follow this skill body for supported account, wallet, and setup routes. No local command runtime is declared.
If the current date is more than 7 days after the last updated date, reinstall this skill from skills.sh or ClawHub before relying on endpoints, schemas, setup steps, or examples.
What This Tool Does
Analyze any stock or cryptocurrency with professional-grade trading signal diagnostics powered by multi-indicator technical analysis. Feed in OHLCV price data and get back actionable buy and sell signals, strategy backtests with historical performance metrics, and detailed risk analytics including maximum adverse excursion, maximum favorable excursion, win rate, expectancy, and drawdown analysis. Identify trend and momentum regimes, evaluate signal strength across multiple timeframes, and export publication-ready analysis charts and trade logs. Perfect for systematic traders building quantitative strategies, portfolio managers evaluating entry and exit timing, crypto analysts screening for momentum setups, and researchers backtesting technical indicators against real market data.
Product Instructions
Trading Signal Analysis
Advanced signal detection, backtesting, and risk analytics engine for stock and crypto OHLCV data. Computes technical indicators, detects trading signals, runs strategy backtests with MAE/MFE analysis, and generates downloadable charts and trade logs.
Actions
analyze_signals
Detect trading signals from OHLCV candle data. Computes SMA, EMA, RSI, MACD, Bollinger Bands, ATR, breakout levels, and volume analysis. Returns signal counts, recent signal events, and current indicator values.
Required:candles (array of OHLCV objects, minimum 30 rows)
expiration_days -- File retention 1-7 days (default: 7)
chart_width / chart_height -- Chart dimensions in pixels
Performance Metrics
Backtest results include:
total_trades, wins, losses, win_rate_pct
total_return_pct, final_equity
max_drawdown_pct
expectancy_pct -- Average trade return
profit_factor -- Sum of wins / sum of losses
sharpe -- Annualized Sharpe ratio
sortino -- Annualized Sortino ratio
average_trade_mae_pct -- Average Maximum Adverse Excursion
average_trade_mfe_pct -- Average Maximum Favorable Excursion
average_bars_held -- Average trade duration
Important Notes
Candle data must have at least 30 rows; more rows than the largest indicator window + 2.
sma_fast must be less than sma_slow; ema_fast must be less than ema_slow.
rsi_oversold must be less than rsi_overbought.
Transaction costs are applied as basis points per side (default 5 bps = 0.05%).
Set periods_per_year to match your data frequency (252 for daily, 8760 for hourly).
Charts are stored in cloud storage with signed download URLs.
When To Use
Use this skill for Trading Signal Analysis on AgentPMT.
Use it when an agent needs this specific tool's behavior, schema, inputs, outputs, and invocation shape.
Search and activation keywords: trading signal analysis, generate buy and sell trading signals from technical indicators, backtest trading strategies against historical ohlcv price data, analyze maximum adverse excursion and maximum favorable excursion for trade risk, calculate win rate and expectancy for systematic trading strategies, analyze signals, candles, symbol.
No categories or industry tags are published for this tool.
Actions And Schema
Complete generated action schema: ./schema.md.
Supported action count: 3.
x402 availability: not enabled for this product.
analyze_signals (action slug: analyze-signals): Detect trading signals from OHLCV data using SMA/EMA crossovers, RSI, MACD, Bollinger Bands, breakouts, and volume spikes. Returns signal counts, recent events, and latest indicator values. Price: 6 credits. Parameters: atr_period, bollinger_period, bollinger_stddev, breakout_lookback, candles, ema_fast, ema_slow, macd_signal_period, plus 10 more.
backtest_strategy (action slug: backtest-strategy): Backtest a trading strategy on OHLCV data. Returns trade log, equity curve, and performance metrics (win rate, Sharpe, Sortino, drawdown, MAE/MFE). Price: 6 credits. Parameters: atr_period, bollinger_period, bollinger_stddev, breakout_lookback, candles, ema_fast, ema_slow, include_short, plus 17 more.
full_analysis (action slug: full-analysis): Run both signal analysis and strategy backtest, generate downloadable charts and trade log CSV. Price: 6 credits. Parameters: atr_period, bollinger_period, bollinger_stddev, breakout_lookback, candles, chart_height, chart_width, ema_fast, plus 24 more.
Live Schema And Examples
Use the compact schema above for ordinary calls. Before a new production integration, or whenever parameters, enum values, nested objects, outputs, or examples are unclear, fetch live details first.
Exact schema: call agentpmt-tool-search-and-execution with action: "get_schema", and tool_id: "trading-signal-analysis".
Detailed examples: call agentpmt-tool-search-and-execution with action: "get_instructions" and tool_id: "trading-signal-analysis", or call this product with action: "get_instructions" when the product tool is already selected.
Treat returned live schema and instructions as more specific than this generated summary.
MCP schema lookup through the main AgentPMT MCP server:
AgentPMT account route: first use ../agentpmt-account-mcp-rest-api-setup to connect the main MCP server or REST API for an Agent Group where this tool is enabled.
x402 route: not enabled for this product.
AgentPMT overview: use ../what-is-agentpmt for marketplace, Agent Group, workflow, MCP, REST, and payment concepts.
If those setup skills are not installed beside this product skill, use the downloads below.
