Modular Market Brief

PassAudited by VirusTotal on May 12, 2026.

Overview

Type: OpenClaw Skill Name: modular-market-brief Version: 0.1.0 The skill bundle is designed to generate market reports, utilizing Python scripts to fetch financial data from legitimate public sources like Yahoo Finance and TMX Money, and via the yfinance library. The `SKILL.md` provides instructions for setting up a Python virtual environment and running these scripts, which is a standard and safe practice. There is no evidence of data exfiltration, malicious execution, persistence, or prompt injection attempts against the agent. All network calls are to known financial data providers and are directly aligned with the skill's stated purpose.

Findings (0)

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.

What this means

Using the optional scripts may install external Python packages, so their source and versions affect the local environment.

Why it was flagged

The skill recommends installing third-party Python packages to enable structured market data fetching. This is disclosed, user-directed, and placed in a virtual environment, but the packages are unpinned.

Skill content
python3 -m venv ~/.venvs/market-brief ... ~/.venvs/market-brief/bin/pip install yfinance pandas numpy
Recommendation

Install only if you need the helper scripts, keep the virtual environment isolated, and consider pinning or reviewing package versions.

What this means

External finance services may receive the requested ticker list, and report quality depends on those providers' availability and data accuracy.

Why it was flagged

The script sends user-selected ticker symbols to yfinance/Yahoo-style market data tooling. This is directly aligned with generating a price tape, but users should understand that ticker queries go to an external data provider.

Skill content
ap.add_argument("--tickers", required=True, help="Space-separated tickers") ... df = yf.download(ticker, period=period, interval="1d", progress=False)
Recommendation

Use only ticker lists you are comfortable querying through public finance data providers and verify important market data independently.