deepsearch-service
基于 LLM 的深度迭代搜索与推理服务。擅长处理复杂问题，通过自动分解查询、多轮迭代检索、信息评估与验证，最终生成全面且结构化的深度分析报告。
npx skills add majiayu000/claude-skill-registry --skill deepsearch-service-lin-a1-skills-agent --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## 功能 基于 LLM 的迭代式深度搜索服务，能够： 1. 将复杂问题分解为多个子查询 2. 迭代搜索收集多源信息 3. 评估信息充分性，动态调整搜索策略 4. 综合生成结构化分析报告 ## 适用场景 - 复杂问题需要多角度分析 - 需要综合多个来源的信息 - 要求生成完整的研究报告 ## 调用方式 ```python from services.deepsearch_service.client import DeepSearchClient client = DeepSearchClient() # 健康检查 status = client.health_check() # 深度搜索（默认参数） result = client.search("Python异步编程的最佳实践有哪些？") # 自定义参数 result = client.search( query="如何设计一个高可用的微服务架构？", max_iterations=3, # 最大迭代次数 (1-5) queries_per_iteration=3, # 每轮查询数 (1-5) depth_level="deep" # 搜索深度: quick/normal/deep ) # 获取报告和来源 print(result["report"]) for source in result["sources"]: print(f"- {source['title']}: {source['url']}") ``` ## 返回格式 ```json { "query": "Python异步编程的最佳实践有哪些？", "report": "# Python异步编程最佳实践\n\n## 1. 核心概念...", "sources": [ { "title": "Python官方asyncio文档", "url": "https://docs.python.org/...", "relevance": 0.95, "snippet": "asyncio是Python标准库中的异步I/O框架..." } ], "iterations": [ { "iteration": 1, "queries": ["Python asyncio 教程", "async await 用法"], "results_count": 6, "key_findings": ["asyncio是标准库组件"] } ], "total_iterations": 2, "total_sources": 8, "elapsed_seconds": 45.32, "search_timestamp": "2025-12-28T18:30:00" } ``` ## 与 websearch_service 的区别 | 特性 | WebSearch |
- 功能
- 适用场景
- 调用方式
- 返回格式
- 与 websearchservice 的区别
What does the deepsearch-service skill do?
基于 LLM 的深度迭代搜索与推理服务。擅长处理复杂问题，通过自动分解查询、多轮迭代检索、信息评估与验证，最终生成全面且结构化的深度分析报告。
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill deepsearch-service-lin-a1-skills-agent --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.