Dividend Growth Pullback Screener
PassAudited by ClawScan on May 1, 2026.
Overview
This appears to be a coherent stock-screening skill, but it uses third-party finance API keys and produces investment-oriented recommendations that users should review carefully.
Before installing, confirm you are comfortable running the bundled Python script, using FMP/FINVIZ API keys, and letting the skill generate stock-screening recommendations. Protect API keys, review the generated reports critically, and do not treat the output as guaranteed or personalized financial advice.
Findings (3)
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 or FINVIZ API key may be used to make requests against those services, potentially consuming quota or exposing the key if handled carelessly.
The skill expects third-party finance API credentials and can accept them through environment variables or command-line arguments. This is purpose-aligned for market data access, but users should notice that credentials are involved.
export FMP_API_KEY=your_fmp_key_here export FINVIZ_API_KEY=your_finviz_key_here ... python3 screen_dividend_growth_rsi.py --use-finviz --fmp-api-key YOUR_FMP_KEY --finviz-api-key YOUR_FINVIZ_KEY
Use provider-scoped API keys, prefer environment variables or a secret manager over command-line arguments, and rotate keys if accidentally pasted into logs or shell history.
The skill may not run in a clean environment without Python and required packages, and dependency setup is not captured in the registry metadata.
The skill is described as having no install spec, but its normal workflow runs a local Python script. The visible script also imports the external requests package, so users may need to validate local dependencies themselves.
cd dividend-growth-pullback-screener/scripts python3 screen_dividend_growth_rsi.py --use-finviz
Review the bundled script before running it and install dependencies from trusted package sources in an isolated environment.
Users could make real investment decisions based on generated screening reports and may experience financial losses if market conditions or data are wrong.
The skill’s output is intended to influence investment decisions. This is consistent with the stated purpose, but the recommendation framing could be over-trusted if treated as personalized financial advice.
**Investment Recommendation:** - Entry timing assessment (immediate vs. wait for confirmation) - Risk factors specific to the stock - Upside scenarios based on dividend growth compounding
Use the output as one research input only, verify data independently, and consult qualified financial advice before trading.