baidu scholar search

**Quick judgment**: This is a focused, practical skill for keyword-based academic search on Baidu Scholar, especially valuable for Chinese-language literature. It’s well-suited as a retrieval backend for LLM research assistants that need to surface relevant papers and optionally pull abstracts. **Strengths & benefits** - Strong for Chinese literature; also supports English queries. - Simple parameters (`keyword`, `pageNum`, `enable_abstract`) and clear defaults make it easy to control depth vs. latency. - Returns structured metadata and optional abstracts that LLMs can summarize or analyze. - Good fit for use cases like quick topic scans, initial literature review, and bilingual research support. **Key limitations & risks** - Coverage is limited to what Baidu Scholar indexes; not a complete substitute for domain databases (e.g., PubMed, arXiv, specialized conference sites). - When abstracts are enabled, responses may be slower and larger, which can impact latency and token usage in LLM applications. - Requires a BAIDU_API_KEY and sends queries to Baidu’s API, so developers must consider data privacy, API quotas, and regional availability. - Results do not guarantee peer-review quality or absence of retracted/obsolete work; the LLM or user must critically evaluate sources. **Recommended scenarios** - LLM-powered research assistants serving users who read Chinese and need access to Chinese academic literature. - Tools that first search with no abstracts for speed, then selectively re-query with `enable_abstract=true` for papers the user wants to understand in detail. - Education and study helpers that suggest relevant papers and then summarize abstracts for learners, while clearly labeling content as informational, not authoritative medical or legal advice.