trading-indicators-from-price-data — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited trading-indicators-from-price-data (Agent Skill) and scored it 96/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 1 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 1 flagged
The text {match} tells the agent to skip the normal "ask the user first" gate. Used adversarially it removes the human-in-the-loop check before destructive or sensitive actions, turning a normally-gated agent into a fire-and-forget executor.
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Calculate 20 widely used trading indicators from OHLCV candles (open, high, low, close, volume) using Python.
This skill is useful for:
Install dependencies:
pip install pandas pandas-taInput data must include these columns:
openhighlowclosevolumeNaN).You have a trading-indicators skill.
When given OHLCV price data, calculate the following 20 indicators:
RSI(14), MACD line/signal/histogram (12,26,9), SMA(20), SMA(50), EMA(20), EMA(50), WMA(20),
Bollinger upper/middle/lower (20,2), Stoch %K/%D (14,3,3), ATR(14), ADX(14), CCI(20), OBV, MFI(14), ROC(12).
Return a table with the latest value of each indicator and include the last 50 rows when requested.
If data is insufficient, ask for more candles.~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.