Plan, write, and edit professional financial reports; generate finance chart configurations. Use when condensing finance analysis into a structured output.

This package appears to implement a full financial reporting pipeline (prompt templates, chart configs, tool wrappers for news/stock/prediction data, DB helpers and forecasting code). That is coherent with its stated purpose — but there are several practical and security concerns you should resolve before installing or running it: - Missing runtime spec: The skill lists no install steps or Python/package requirements but imports pandas, pydantic, agno.tools, loguru, and other non-standard modules. Ask the author for a requirements.txt or an install script and for Python version guidance. - Undeclared external access and credentials: The code calls news/Polymarket/stock toolkits and fetches web content and updates a database. Ask which external services are contacted, whether API keys are required, and where credentials should be stored. Do not supply high-privilege credentials (AWS, GCP, database admin) unless the author justifies them. - Review network-facing modules: Inspect scripts/utils/news_tools.py, scripts/utils/stock_tools.py, scripts/utils/search_tools.py, and scripts/utils/database_manager.py to see what endpoints are used, what data is uploaded, and how requests are authenticated. Look for any hardcoded endpoints or unexpected external domains. - Sandbox first: Run the skill in an isolated environment (container or VM) with no access to sensitive networks/credentials. Verify behavior (which hosts are contacted, DB writes) before using it with any real data. - Verify provenance: The skill has no homepage and an unknown source; prefer code from known maintainers. Ask the publisher for a README, license, changelog, and list of required environment variables and resources. - If you must use it: Provide only minimal, least-privilege credentials (if any), and a dedicated local database; monitor outbound connections and logs. If unsure, have a developer or security person audit the network/data-access code before trusting it with sensitive information.

Type: OpenClaw Skill Name: alphaear-reporter Version: 1.0.0 The alphaear-reporter skill bundle is a legitimate and well-structured financial analysis and reporting tool. It integrates news aggregation via NewsNow and Jina AI, stock market data via Akshare, and a custom time-series prediction model (Kronos). The code utilizes the Agno (formerly Phidata) framework for agent orchestration and Pyecharts for financial visualization. While the tool requires network access for research and local SQLite database access for caching, these capabilities are strictly aligned with its stated purpose. Security best practices are observed, such as using 'ast.literal_eval' instead of 'eval' in 'scripts/utils/json_utils.py' and employing parameterized SQL queries in 'scripts/utils/database_manager.py'. No evidence of data exfiltration, malicious prompt injection, or unauthorized execution was found.