企业级SEO工具，提供关键词研究、内容优化、排名追踪及自动内链建议，助力提升网站搜索排名和流量。

This package contains self-contained JS modules for SEO tasks but most network-dependent functionality is mocked/stubbed. Key points to consider before installing or paying: - Functionality mismatch: Content fetching and web search are stubbed; analyzing a real URL will not retrieve the actual page content nor perform live Google SERP queries. The README/SKILL.md marketing ("based on latest Google algorithms", "real-time competition analysis") is misleading relative to the code. - Source / trust: Source/homepage are unknown or placeholders ([email protected], docs.example.com). The repository URL in metadata is generic. Verify the author's identity and a trustworthy upstream repository before use in production. - Low technical risk: There are no external downloads, no required environment variables, and no obvious data-exfiltration code. Still, because the implementation is mocked, do not rely on it for real SEO measurements. - Actions you can take: (1) Ask the author for a link to the canonical repo or a demo that shows live search integration. (2) Inspect or run the code in a sandbox to confirm network behavior — check whether _fetchContent and _performSearch get replaced/implemented. (3) If you need real live data, require explicit evidence of real search API integration and credentials handling (and ensure any credentials are scoped and stored securely). (4) Avoid paying or integrating this as an enterprise service until the live-data behavior is confirmed. If you want, I can: (a) point out the exact lines that are mocked/stubbed, (b) suggest minimal code changes to add real HTTP fetches and where to insert API keys, or (c) produce a checklist of signals to verify a trustworthy SEO skill/provider.

Type: OpenClaw Skill Name: ai-seo-optimizer-lvjunjie Version: 1.0.0 The AI-SEO-Optimizer skill bundle is a simulated SEO analysis engine that uses mock data and randomized heuristics to provide keyword research, content optimization, and rank tracking. Analysis of the source code (index.js and the src/ directory) reveals no actual network exfiltration, file system access, or malicious execution patterns; most functions like _performSearch and _getRanking are placeholders returning hardcoded or random values. The SKILL.md and README.md files contain standard operational instructions without any evidence of harmful prompt injection or attempts to bypass security controls.