Skill flagged — suspicious patterns detected
ClawHub Security flagged this skill as suspicious. Review the scan results before using.
Predict
v1.0.0Prediction and forecasting system for trends, outcomes, and risks. Use when user mentions predictions, forecasts, trends, scenarios, or future outcomes. Anal...
⭐ 0· 248·0 current·0 all-time
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
high confidencePurpose & Capability
The skill's name and description promise forecasting, model building, scenario generation, probability evaluation, and accuracy tracking. The bundle only includes one simple script (forecast_trend.py) that prints a static forecasting framework and saves a short metadata record; it does not build models or read input data. SKILL.md references many other scripts and reference files that are not present, which is inconsistent with the stated capabilities.
Instruction Scope
SKILL.md instructs running multiple scripts (generate_scenarios.py, assess_risk.py, evaluate_probability.py, etc.) and passing data files (e.g., --data "historical.csv"), but those scripts are absent and forecast_trend.py doesn't accept a --data argument or read data. The instructions therefore overreach the actual runtime behavior and would likely produce runtime errors or silently do less than promised.
Install Mechanism
No install specification or external downloads are included (instruction-only with one script). This minimizes supply-chain risk; nothing is fetched or executed from remote URLs during install.
Credentials
The skill requests no environment variables or credentials. The included script writes to a local path (~/.openclaw/workspace/memory/predict), which aligns with SKILL.md's claim that prediction data is stored locally, though SKILL.md earlier referenced memory/predict/ (path mismatch is minor but noted).
Persistence & Privilege
The skill does not request permanent/always inclusion and does not require extra privileges. It will create a directory and write forecasts.json under the user's home workspace (~/.openclaw/workspace/memory/predict), so expect persistent local storage of generated forecast records.
What to consider before installing
Do not assume this skill will perform the complex forecasting the description promises. What you have is a minimal script that prints template guidance and appends a short forecast record to ~/.openclaw/workspace/memory/predict/forecasts.json. Before installing or running: (1) Ask the author for the missing scripts (generate_scenarios.py, assess_risk.py, evaluate_probability.py, references/*) or a corrected SKILL.md; (2) Inspect those scripts to confirm they actually read and process data and do not contact external endpoints; (3) If you must run it, do so in a sandboxed environment and back up/monitor the ~/.openclaw/workspace/memory/predict directory to avoid unexpected file writes; (4) Prefer an updated package where declared capabilities match included code. If the author supplies the missing files and they perform as advertised (no unexpected network calls, proper data handling), this assessment could change to benign.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.