Pair Trade Screener
PassAudited by ClawScan on May 1, 2026.
Overview
The artifacts describe a coherent stock pair-analysis tool with no hidden or destructive behavior, but it does require user-managed Python dependencies and an FMP API key.
Before installing, use a Python virtual environment, verify or pin dependencies, and keep your FMP API key private. Treat the trading signals as research support rather than guaranteed investment advice; the artifacts do not show any automatic trading or account changes.
Findings (2)
Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.
Your FMP API key is needed for market data access and could be exposed if pasted into shared logs, shell history, or a shared shell profile.
The skill needs a Financial Modeling Prep API credential and suggests optional shell-profile storage. This is expected for the stated market-data purpose, but users should treat the key as a credential.
export FMP_API_KEY="your_key_here" Or add to `~/.bashrc` / `~/.zshrc` for persistence.
Prefer an environment variable over command-line key entry, keep the key out of shared logs, and rotate it if exposed. The skill metadata should ideally declare the FMP API key requirement.
Installing dependencies trusts the current package sources and versions, which can affect reproducibility and supply-chain assurance.
The setup uses user-directed, unpinned Python package installation. These packages are common and purpose-aligned, but unpinned installs depend on whatever versions the package index resolves at install time.
pip install pandas numpy scipy statsmodels requests
Install in a virtual environment, use trusted package indexes, and pin or record dependency versions for repeatable use.