Web Search
fastclaw-ai/fastclaw
Search the web and fetch web pages. An agent skill from fastclaw-ai/fastclaw.
深度研究代理系统社区版，对复杂主题进行多轮迭代的网络搜索和综合分析。使用场景：当用户需要对特定主题进行深入、全面的研究时，特别是需要基于最新网络信息生成详细分析报告的情况。支持多轮迭代搜索、智能搜索方向调整和综合分析报告生成。本skill是一个工作流描述文档，没有执行脚本，依赖web-search skill进行网页搜索。
Install Deepsearch
$ npx skills add huangruiteng/CS-Notes --skill deepsearch -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install huangruiteng/CS-Notes deepsearch --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/huangruiteng/CS-Notes.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.trae/openclaw-skills/deepsearch .claude/skills/deepsearch && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "deepsearch" agent skill from https://github.com/huangruiteng/CS-Notes/tree/master/.trae/openclaw-skills/deepsearch into .claude/skills/deepsearch/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deepsearch", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/huangruiteng/CS-Notes/tree/master/.trae/openclaw-skills/deepsearchType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add huangruiteng/CS-Notes --skill deepsearch -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install huangruiteng/CS-Notes deepsearch --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/huangruiteng/CS-Notes.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.trae/openclaw-skills/deepsearch .agents/skills/deepsearch && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "deepsearch" agent skill from https://github.com/huangruiteng/CS-Notes/tree/master/.trae/openclaw-skills/deepsearch into .agents/skills/deepsearch/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deepsearch", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add huangruiteng/CS-Notes --skill deepsearch -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install huangruiteng/CS-Notes deepsearch --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/huangruiteng/CS-Notes.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.trae/openclaw-skills/deepsearch .cursor/skills/deepsearch && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "deepsearch" agent skill from https://github.com/huangruiteng/CS-Notes/tree/master/.trae/openclaw-skills/deepsearch into .cursor/skills/deepsearch/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deepsearch", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/huangruiteng/CS-Notes.git --path .trae/openclaw-skills/deepsearch--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add huangruiteng/CS-Notes --skill deepsearch -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install huangruiteng/CS-Notes deepsearch --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/huangruiteng/CS-Notes.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.trae/openclaw-skills/deepsearch .gemini/skills/deepsearch && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "deepsearch" agent skill from https://github.com/huangruiteng/CS-Notes/tree/master/.trae/openclaw-skills/deepsearch into .gemini/skills/deepsearch/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deepsearch", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install huangruiteng/CS-Notes deepsearchInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add huangruiteng/CS-Notes --skill deepsearch -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/huangruiteng/CS-Notes.git skills-src && mkdir -p .github/skills && cp -r skills-src/.trae/openclaw-skills/deepsearch .github/skills/deepsearch && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "deepsearch" agent skill from https://github.com/huangruiteng/CS-Notes/tree/master/.trae/openclaw-skills/deepsearch into .github/skills/deepsearch/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deepsearch", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add huangruiteng/CS-Notes --skill deepsearch -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install huangruiteng/CS-Notes deepsearch --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/huangruiteng/CS-Notes.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.trae/openclaw-skills/deepsearch .opencode/skills/deepsearch && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "deepsearch" agent skill from https://github.com/huangruiteng/CS-Notes/tree/master/.trae/openclaw-skills/deepsearch into .opencode/skills/deepsearch/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deepsearch", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
deepsearch- GitHub stars
- 4k
- Token cost
- ~977 tokens
- SKILL.md length
- 249 words
- Files
- 2
- Skills in repo
- 39
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
深度研究代理系统社区版，对复杂主题进行多轮迭代的网络搜索和综合分析。使用场景：当用户需要对特定主题进行深入、全面的研究时，特别是需要基于最新网络信息生成详细分析报告的情况。支持多轮迭代搜索、智能搜索方向调整和综合分析报告生成。本skill是一个工作流描述文档，没有执行脚本，依赖web-search skill进行网页搜索。
- Works in 5 steps: 输入接收阶段 → 初始化阶段 → 迭代搜索阶段（多轮执行） → …
- Tasks that involve Web search
- SKILL.md covers 概述, 工作流调用逻辑, 使用场景 and 技术特点, plus 3 more sections
- Calls python
What it does
Deepsearch is an agent skill from huangruiteng/CS-Notes. 深度研究代理系统社区版，对复杂主题进行多轮迭代的网络搜索和综合分析。使用场景：当用户需要对特定主题进行深入、全面的研究时，特别是需要基于最新网络信息生成详细分析报告的情况。支持多轮迭代搜索、智能搜索方向调整和综合分析报告生成。本skill是一个工作流描述文档，没有执行脚本，依赖web-search skill进行网页搜索。
Its SKILL.md is about 980 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file.
It sits in Productivity & Automation, covering Web search. It works with Python. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Web search
Example prompts
- “/deepsearch”
Requirements
- Python 3
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit f7b4e92. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Deepsearch loads about 977 tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 249 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from huangruiteng/CS-Notes at commit f7b4e92, republished under its Apache-2.0 licence (© huangruiteng). 249 words, ~977 tokens.
Download SKILL.mdSave it as
.claude/skills/deepsearch/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- deepsearch
- description
- 深度研究代理系统社区版，对复杂主题进行多轮迭代的网络搜索和综合分析。使用场景：当用户需要对特定主题进行深入、全面的研究时，特别是需要基于最新网络信息生成详细分析报告的情况。支持多轮迭代搜索、智能搜索方向调整和综合分析报告生成。本skill是一个工作流描述文档，没有执行脚本，依赖web-search skill进行网页搜索。
- license
- Complete terms in LICENSE.txt
DeepSearch
概述
深度研究代理系统社区版是一个基于工作流的深度研究系统，能够对复杂主题进行多轮迭代的网络搜索和综合分析。系统通过结合LLM智能分析和实时网络搜索，生成详细的研究报告。
工作流调用逻辑
系统架构
本系统是一个工作流描述文档，没有执行脚本。依赖以下外部技能：
- web-search skill: 用于执行网页搜索，运行脚本：
python scripts/web_search.py "<query>" - LLM技能: 用于智能分析和推理
工作流程
1. 输入接收阶段
- 用户输入: 研究主题（sys.query）和研究深度（depth）
- 默认深度: 3（可配置）
2. 初始化阶段
- 创建迭代数组，深度为指定的depth值
- 数组格式：
[0, 1, ..., depth-1]
3. 迭代搜索阶段（多轮执行）
每轮迭代执行以下步骤：
a) LLM智能分析
- 使用LLM分析当前研究状态
- 输入：用户查询、已收集的findings、已搜索的topics
- 输出：JSON格式，包含：
nextSearchTopic: 下一个搜索主题（字符串或None）shouldContinue: 是否继续搜索（布尔值）
b) JSON解析
- 提取
nextSearchTopic和shouldContinue字段 - 更新对话变量
c) 条件判断
- 如果
shouldContinue为True：- 执行web-search：
python scripts/web_search.py "<nextSearchTopic>" - 将搜索结果追加到findings数组
- 更新搜索进度显示
- 继续下一轮迭代
- 执行web-search：
- 如果
shouldContinue为False：- 结束当前迭代
- 输出中间结果
d) 变量管理
- 更新
nextSearchTopic和shouldContinue变量 - 将
nextSearchTopic追加到topics数组（记录已搜索主题） - 避免重复搜索相同主题
4. 综合分析阶段
- 所有迭代完成后，使用LLM综合分析所有收集到的findings
- 生成详细的综合分析报告
- 输出格式：Markdown格式的详细报告
5. 报告生成阶段
- 输出最终的研究分析结果
- 包含重要洞察、结论和剩余不确定性
- 适当引用来源
变量说明
系统维护以下对话变量：
| 变量名 | 类型 | 描述 |
|---|---|---|
topics | array[string] | 已搜索的主题列表 |
nextSearchTopic | string | 下一个要搜索的主题 |
findings | array[string] | 收集到的搜索结果列表 |
shouldContinue | string | 是否继续搜索的标志 |
网页搜索集成
当需要进行网络搜索时：
- 使用
nextSearchTopic作为查询参数 - 运行web-search技能：
python scripts/web_search.py "<query>" - 根据返回的摘要列表组织答案，不新增或臆造内容
- 将搜索结果追加到
findings数组
注意: 不要使用任何搜索参数配置（如search_depth、topic、max_results、country、time_range、days等），仅保留核心输入query。
进度跟踪
系统实时显示搜索进度：
- 格式：
{index + 1}/{depth}th search executed. - 例如：
1/3th search executed.
使用场景
适用场景
- 复杂主题研究: 需要对特定主题进行深入、全面的研究
- 最新信息分析: 需要基于最新网络信息生成详细分析报告
- 多角度探索: 需要从不同角度和维度探索一个主题
- 系统化调查: 需要系统化的调查和证据收集
典型用例
- 市场趋势分析
- 技术发展研究
- 竞争对手分析
- 学术文献综述
- 产品调研
技术特点
智能特性
- 自适应搜索: 每轮搜索后由LLM分析结果，智能决定下一步搜索方向
- 避免重复: 系统记录已搜索主题，避免重复搜索相同内容
- 深度推理: 使用专门的推理模型进行综合分析
系统特性
- 多轮迭代: 支持指定深度的多轮搜索
- 并行能力: 支持最多10个并行搜索
- 状态管理: 完整的变量管理和状态跟踪
- 进度可视: 实时显示搜索进度和状态
集成特性
- LLM集成: 结合GPT-4o进行智能分析，deepseek-reasoner进行深度推理
- 网络搜索: 集成web-search技能获取实时网络信息
- JSON处理: 使用JSON解析工具处理结构化数据
工作流示例
输入示例
用户查询: "人工智能在医疗领域的最新发展"
研究深度: 3执行流程
第1轮:
- LLM分析: 决定搜索"AI医疗诊断最新进展"
- Web搜索: 执行搜索并收集结果
- 状态更新: 记录主题，决定继续搜索
第2轮:
- LLM分析: 基于第1轮结果，决定搜索"医疗影像AI技术突破"
- Web搜索: 执行搜索并收集结果
- 状态更新: 记录主题，决定继续搜索
第3轮:
- LLM分析: 基于前两轮结果，决定搜索"AI药物研发应用"
- Web搜索: 执行搜索并收集结果
- 状态更新: 记录主题，决定结束搜索
综合分析:
- LLM综合分析所有收集到的findings
- 生成关于"人工智能在医疗领域的最新发展"的详细报告
输出示例
# 人工智能在医疗领域的最新发展研究报告
## 执行摘要
[基于三轮搜索的综合分析...]
## 主要发现
1. AI在医疗诊断方面的最新进展
- [具体发现1]
- [具体发现2]
2. 医疗影像AI技术突破
- [具体发现3]
- [具体发现4]
3. AI在药物研发中的应用
- [具体发现5]
- [具体发现6]
## 结论与建议
[综合分析结论...]
## 未来研究方向
[基于研究发现提出的未来研究方向...]注意事项
工作流限制
- 无执行脚本: 本skill是一个工作流描述文档，不包含可执行脚本
- 外部依赖: 依赖web-search技能执行实际搜索
- 参数简化: 搜索时仅使用query参数，忽略其他搜索配置
使用建议
- 深度设置: 根据研究复杂度设置合适的depth值
- 查询优化: 提供清晰具体的研究主题
- 结果验证: 对生成的报告进行必要的事实核查
最佳实践
- 渐进式研究: 从宽泛主题开始，逐步深入具体方向
- 多源验证: 结合多个来源的信息进行交叉验证
- 及时更新: 对于快速发展的主题，建议定期重新研究
故障排除
常见问题
- 搜索无结果: 检查query是否过于具体或专业，尝试更通用的搜索词
- 迭代过早结束: 调整LLM的temperature参数或提供更多上下文
- 结果重复: 系统已内置避免重复机制，如仍出现可手动干预
性能优化
- 并行搜索: 充分利用系统的并行能力（最多10个并行）
- 缓存利用: 对于相同主题的多次研究，可考虑结果缓存
- 增量更新: 对于持续研究，可采用增量更新策略
重要提示: 本skill描述了一个深度研究工作流，实际执行需要依赖外部技能和配置。请确保已正确配置web-search技能和相关LLM服务。
© huangruiteng, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file in .trae/openclaw-skills/deepsearch of huangruiteng/CS-Notes.
- SKILL.md
- LICENSE.txt
Open the folder on GitHubat commit f7b4e92
Compare with similar skills
Deepsearch next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Deepsearch this skillhuangruiteng/CS-Notes | 4k | — | ~977 | Automated safety check: Pass | Apache-2.0 | |
| Web Searchfastclaw-ai/fastclaw | 1.4k | — | ~294 | Automated safety check: Pass | Custom licence | |
| Duckduckgo SearchTommy-yw/RunbookHermes | 546 | 3 repos | ~2.1k | Automated safety check: Pass | MIT | |
| Tavily SearchOpenMinis/MinisSkills | 446 | — | ~869 | Automated safety check: Pass | MIT | |
| Ag2 Use Builtin Toolsag2ai/build-with-ag2 | 252 | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Web Accessitwanger/PaiCLI-Python | 102 | — | ~183 | Automated safety check: Pass | MIT |
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Questions about Deepsearch
What does Deepsearch do?
深度研究代理系统社区版，对复杂主题进行多轮迭代的网络搜索和综合分析。使用场景：当用户需要对特定主题进行深入、全面的研究时，特别是需要基于最新网络信息生成详细分析报告的情况。支持多轮迭代搜索、智能搜索方向调整和综合分析报告生成。本skill是一个工作流描述文档，没有执行脚本，依赖web-search skill进行网页搜索。. Deepsearch is an agent skill from huangruiteng/CS-Notes.
When should I use Deepsearch?
Deepsearch fits situations like: tasks that involve Web search.
How do I install Deepsearch in Claude Code?
Run `npx skills add huangruiteng/CS-Notes --skill deepsearch -a claude-code`. Or copy the skill folder (.trae/openclaw-skills/deepsearch in huangruiteng/CS-Notes) into .claude/skills/deepsearch in your project. Claude Code loads it when a task matches its description.
How do I install Deepsearch in Codex?
Run `npx skills add huangruiteng/CS-Notes --skill deepsearch -a codex`. Or copy the skill folder (.trae/openclaw-skills/deepsearch in huangruiteng/CS-Notes) into .agents/skills/deepsearch in your project. Codex loads it when a task matches its description.
Can I use Deepsearch in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add huangruiteng/CS-Notes --skill deepsearch -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deepsearch, .gemini/skills/deepsearch, .github/skills/deepsearch and .opencode/skills/deepsearch in your project.
What does Deepsearch need to run?
Going by SKILL.md and its folder, Deepsearch needs the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Deepsearch access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Deepsearch safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Deepsearch use?
Deepsearch is published under the Apache-2.0 licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Deepsearch use?
About 977 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Deepsearch?
Skills that share tags, products or a category with Deepsearch: Web Search (fastclaw-ai/fastclaw, 1.4k stars), Duckduckgo Search (Tommy-yw/RunbookHermes, 546 stars), Tavily Search (OpenMinis/MinisSkills, 446 stars) and Ag2 Use Builtin Tools (ag2ai/build-with-ag2, 252 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Deepsearch?
huangruiteng (a GitHub user) maintains it in huangruiteng/CS-Notes, which has 4,001 GitHub stars. The repository holds 39 skills in this directory. The repository was last updated on October 8, 2026.
Source: huangruiteng/CS-Notes on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.