Statistical arbitrage tool for identifying and analyzing pair trading opportunities. Detects cointegrated stock pairs within sectors, analyzes spread behavior, calculates z-scores, and provides entry/exit recommendations for market-neutral strategies. Use when user requests pair trading opportunities, statistical arbitrage screening, mean-reversion strategies, or market-neutral portfolio construction. Supports correlation analysis, cointegration testing, and spread backtesting.
Security Analysis
high confidenceThe skill appears to implement a legitimate pair-trading screener, but its metadata and instructions are inconsistent with the included code (notably an undeclared required FMP API key and mismatched example commands), so you should inspect and test before running or granting credentials.
The skill's name/description (pair-trading screener) matches the included scripts and methodology. However the package metadata declares no required environment variables or primary credential while the README, SKILL.md, and both scripts clearly expect an FMP API key (FMP_API_KEY) or --api-key parameter. That omitted credential in metadata is an incoherence and reduces transparency.
Runtime instructions and SKILL.md direct the agent to fetch historical prices from FinancialModelingPrep and run local analysis scripts (find_pairs.py, analyze_spread.py). This stays within the declared purpose, but SKILL.md and README show at least one example command ('python scripts/fetch_price_data.py') that does not exist in the bundle — a mismatch that indicates sloppy packaging or outdated docs. The scripts only contact financialmodelingprep.com (expected) and read the FMP_API_KEY env var, and do not access other system credentials or unrelated file paths.
No install spec is provided (instruction-only/ship-with-scripts). There are local Python scripts; dependencies are standard Python packages (pandas, numpy, statsmodels, requests). No downloads from untrusted URLs, no extracted archives, and nothing writes system-wide binaries — low install risk.
The code requires an FMP API key (FMP_API_KEY) to run, which is proportional to the task. However the skill metadata lists no required env vars or primary credential — an important omission. The scripts do not request other unrelated secrets, but the missing declration reduces transparency and could cause users to supply credentials without realizing they're needed by the skill.
The skill does not request persistent presence (always:false) and contains no code that modifies other skills or system-level configuration. It runs as ad-hoc Python scripts and prints/writes JSON outputs per the README — no elevated privileges detected.
Guidance
This package mostly matches its claimed purpose (pair-trading screening using FinancialModelingPrep). However: (1) the metadata fails to declare the required FMP API key even though the README, SKILL.md, and both scripts expect FMP_API_KEY (or --api-key). That omission is confusing and should be fixed before trusting the skill. (2) Some example commands in SKILL.md/README reference a non-existent script (fetch_price_data.py), indicating outdated or sloppy docs — review the included scripts (find_pairs.py, analyze_spread.py) yourself. Before running: inspect the Python files to confirm behavior (they call only financialmodelingprep.com and produce local JSON/text output); run them in a sandbox with a low-privilege/test API key; do not supply sensitive or high-privilege credentials beyond an FMP API key; consider running with network access limited to the FMP domain and monitor outbound requests. If you require full assurance, ask the publisher for corrected metadata and documentation or obtain the skill from a known/trusted source.
Latest Release
v0.1.0
Initial release of pair-trade-screener: a statistical arbitrage tool for market-neutral pair trading. - Detects cointegrated stock pairs using correlation and cointegration analysis. - Calculates spread z-scores to identify mean-reversion opportunities. - Generates entry and exit signals for trades based on statistical thresholds. - Recommends position sizing for market-neutral exposure. - Provides workflow for sector-based, custom, or industry-specific screening. - Supports spread analysis, backtesting, and risk management for pair trades.
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