Local Budget

Analyze exported bank/credit card CSV files locally to track spending, categorize transactions with LLM reasoning, compare against user-defined budgets, and...

This skill appears coherent and local-only, but review these practical safety steps before installing: 1) Run the scripts locally on a machine you trust (they process potentially sensitive bank CSVs). 2) Inspect the included Python files yourself if you have doubts — there are no network calls or credential use, so a quick code review is sufficient. 3) When running, keep outputs (categorized.json, report.md) in a directory you control; avoid writing reports into shared/system folders unless intended. 4) The workflow relies on a manual LLM-review step (the agent or you should confirm low/medium confidence items) — do not skip manual review if you care about correct categorization. 5) If your agent platform can autonomously call skills and transmit data externally, ensure agent-level network/external-access policies are appropriate; the skill itself does not perform network exfiltration. If you want higher assurance, run the scripts in a disposable environment (virtualenv / container) and test with redacted sample CSVs first.

Type: OpenClaw Skill Name: nai-local-budget Version: 1.0.0 The local-budget skill bundle is a legitimate tool for analyzing bank and credit card CSV exports locally. It consists of Python scripts (parse_csv.py, categorize.py, report.py) that use standard libraries to process financial data and generate Markdown reports without any network activity or unauthorized file access. No evidence of malicious intent, data exfiltration, or harmful prompt injection was found.