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深度调研方法论（8步法）：将模糊主题转化为高质量调研报告. An agent skill from nexu-io/nexu.
Install Deep Research
$ npx skills add nexu-io/nexu --skill deep-research -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install nexu-io/nexu deep-research --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/nexu-io/nexu.git skills-src && mkdir -p .claude/skills && cp -r skills-src/apps/desktop/static/bundled-skills/deep-research .claude/skills/deep-research && 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 "deep-research" agent skill from https://github.com/nexu-io/nexu/tree/main/apps/desktop/static/bundled-skills/deep-research into .claude/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", 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/nexu-io/nexu/tree/main/apps/desktop/static/bundled-skills/deep-researchType 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 nexu-io/nexu --skill deep-research -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install nexu-io/nexu deep-research --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nexu-io/nexu.git skills-src && mkdir -p .agents/skills && cp -r skills-src/apps/desktop/static/bundled-skills/deep-research .agents/skills/deep-research && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "deep-research" agent skill from https://github.com/nexu-io/nexu/tree/main/apps/desktop/static/bundled-skills/deep-research into .agents/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", 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 nexu-io/nexu --skill deep-research -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install nexu-io/nexu deep-research --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nexu-io/nexu.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/apps/desktop/static/bundled-skills/deep-research .cursor/skills/deep-research && 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 "deep-research" agent skill from https://github.com/nexu-io/nexu/tree/main/apps/desktop/static/bundled-skills/deep-research into .cursor/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", 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/nexu-io/nexu.git --path apps/desktop/static/bundled-skills/deep-research--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 nexu-io/nexu --skill deep-research -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install nexu-io/nexu deep-research --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nexu-io/nexu.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/apps/desktop/static/bundled-skills/deep-research .gemini/skills/deep-research && 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 "deep-research" agent skill from https://github.com/nexu-io/nexu/tree/main/apps/desktop/static/bundled-skills/deep-research into .gemini/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", 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 nexu-io/nexu deep-researchInstalls 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 nexu-io/nexu --skill deep-research -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/nexu-io/nexu.git skills-src && mkdir -p .github/skills && cp -r skills-src/apps/desktop/static/bundled-skills/deep-research .github/skills/deep-research && 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 "deep-research" agent skill from https://github.com/nexu-io/nexu/tree/main/apps/desktop/static/bundled-skills/deep-research into .github/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", 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 nexu-io/nexu --skill deep-research -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install nexu-io/nexu deep-research --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nexu-io/nexu.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/apps/desktop/static/bundled-skills/deep-research .opencode/skills/deep-research && 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 "deep-research" agent skill from https://github.com/nexu-io/nexu/tree/main/apps/desktop/static/bundled-skills/deep-research into .opencode/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", 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
deep-research- GitHub stars
- 3.3k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 444 words
- Files
- 5
- Skills in repo
- 10
- Repo updated
- First seen
- Licence
- MIT
At a glance
深度调研方法论（8步法）：将模糊主题转化为高质量调研报告. An agent skill from nexu-io/nexu.
- Works in 11 steps: 问题类型判断 → 5: 时效敏感性判断（BLOCKING） → 问题拆解与边界界定 → …
- Tasks that involve Deep research
- SKILL.md covers 核心理念, 参考文档, 工作目录结构 and 资料分层, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Deep Research is an agent skill from nexu-io/nexu. 深度调研方法论（8步法）：将模糊主题转化为高质量调研报告。 触发词：/deep-research、深度调研、帮我调研、调研一下、对比分析 注意：如果用户需要的是可视化图谱而非报告，请使用 research-to-diagram skill。
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files (for example `templates/comparison-framework.md`, `templates/fact-card.md` and `templates/intermediate-outputs.md`).
It sits in Research & Science, covering Deep research and Messaging and chat bots. It works with WeChat, Feishu (Lark) and Slack. The repository describes itself as: The simplest desktop client for OpenClaw 🦞 — bridge your Agent to WeChat, Feishu, Slack & Discord in one click. Works with Claude Code, Codex & any LLM. BYOK, Oauth… The licence is MIT.
When your agent uses it
- Tasks that involve Deep research
- Tasks that involve Messaging and chat bots
Example prompts
- “/deep-research”
Workflow steps
11 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 dadfb1c. 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
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
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
Deep Research loads about 1.6k tokens when it runs. Until then it costs about 34 tokens; SKILL.md has 444 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 nexu-io/nexu at commit dadfb1c, republished under its MIT licence (© nexu-io). 444 words, ~1,596 tokens.
Download SKILL.mdSave it as
.claude/skills/deep-research/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- deep-research
- description
- 深度调研方法论（8步法）：将模糊主题转化为高质量调研报告。 触发词：/deep-research、深度调研、帮我调研、调研一下、对比分析 注意：如果用户需要的是可视化图谱而非报告，请使用 research-to-diagram skill。
- catalog-name
- Deep Research
Deep Research（深度调研 8 步法）
将用户提出的模糊主题，通过系统化方法转化为高质量、可交付的调研报告。
核心理念
- 结论来自机制对比，不是「我感觉像」
- 先钉牢事实，再做推导
- 资料权威优先：L1 > L2 > L3 > L4
- 中间结果必须保存，便于回溯和复用
参考文档
| 文档 | 内容 |
|---|---|
templates/intermediate-outputs.md | 中间产物格式模板 |
templates/comparison-framework.md | 对比框架模板 |
templates/fact-card.md | 事实卡片模板 |
templates/report-structure.md | 报告结构模板 |
工作目录结构
~/Downloads/research/<topic>/
├── 00_问题拆解.md # Step 0-1 产出
├── 01_资料来源.md # Step 2 产出
├── 02_事实卡片.md # Step 3 产出
├── 03_对比框架.md # Step 4 产出
├── 04_推导过程.md # Step 6 产出
├── 05.5_校验记录.md # Step 6.5 产出（独立 Agent 校验）
├── 05_验证记录.md # Step 7 产出
├── FINAL_调研报告.md # Step 8 产出
└── raw/ # 原始资料存档中间产物格式详见 templates/intermediate-outputs.md
资料分层
| 层级 | 资料类型 | 可信度 |
|---|---|---|
| L1 | 官方文档、论文、规范、RFC | ✅ 高 |
| L2 | 官方博客、技术演讲、白皮书 | ✅ 高 |
| L3 | 权威媒体、专家解读、教程 | ⚠️ 中 |
| L4 | 社区讨论、个人博客、论坛 | ❓ 低 |
L4 社区来源（产品对比调研必查）：GitHub Issues/Discussions、Reddit、Hacker News
执行流程（8 步法）
每步完成后，立即写入对应文件。
Step 0: 问题类型判断
| 问题类型 | 核心任务 | 侧重维度 |
|---|---|---|
| 概念对比型 | 建立对比框架 | 机制差异、适用边界 |
| 决策支持型 | 权衡取舍 | 成本、风险、收益 |
| 趋势分析型 | 梳理演进脉络 | 历史、驱动因素、预测 |
| 问题诊断型 | 根因分析 | 症状、原因、证据链 |
| 知识梳理型 | 系统整理 | 定义、分类、关系 |
Step 0.5: 时效敏感性判断（BLOCKING）
| 敏感级别 | 典型领域 | 资料时间窗口 |
|---|---|---|
| 🔴 极高 | AI/大模型、区块链 | 3-6 个月 |
| 🟠 高 | 云服务、前端框架 | 6-12 个月 |
| 🟡 中 | 编程语言、数据库 | 1-2 年 |
| 🟢 低 | 算法原理、设计模式 | 无限制 |
🔴 极高敏感领域强制规则：
- 搜索时带时间约束（
time_range: "month"） - 官方源优先（文档、博客、Changelog）
- 版本号强制标注（禁止「最新版本支持」）
- 超过 6 个月的博客仅作历史参考
- 关键信息至少 2 个独立来源确认
- 直接访问官方下载页面验证（不依赖搜索缓存）
- 搜索产品支持的协议名称（MCP、ACP 等）
Step 1: 问题拆解与边界界定
把模糊主题拆成 2-4 个可调研的子问题，并明确研究对象边界（人群/地域/时间/层级）。
→ 保存：00_问题拆解.md
Step 2: 资料分层与权威锁定
搜索策略（高敏感领域）：
- 官方源定向搜索（限定官方域名）
- 官方下载页面直接验证（BLOCKING）
- 协议/功能名称搜索（BLOCKING）
- 限时广泛搜索
- 版本核实
- 社区声音挖掘（GitHub Issues、Reddit）
适用对象核查（BLOCKING）：收录资料前必须验证适用对象与研究边界匹配。
→ 保存：01_资料来源.md（持续更新）
Step 3: 事实抽取与证据卡片
把资料转化为可核验事实卡片，区分「官方说的」和「我推测的」。
→ 保存：02_事实卡片.md（持续更新）
Step 4: 建立对比/分析框架
根据问题类型选择固定维度：
- 通用：目标、机制、输入输出、优劣势、适用场景、成本收益
- 概念对比：定义、触发方式、执行主体、确定性、资源管理、安全边界
- 决策支持：实现成本、维护成本、风险、收益、团队能力要求
→ 保存：03_对比框架.md
Step 5: 参照物基准对齐
确保对比各方定义稳定、公认、无歧义。
Step 6: 从事实到结论的推导链
显式写出「事实 → 对照 → 结论」的推导过程，每个结论都能追溯到具体事实。
⚠️ 推导防护：结论不得悄悄升级事实卡片中的确定性层级。
- 事实卡片写「可能」→ 结论不得写「会」
- 事实卡片写「理论上」→ 结论不得写「实际上」
- 事实卡片 A 说「只有 X 被禁」+ 事实卡片 B 说「Y 可能受影响」→ 结论不得写「X 和 Y 都被禁了」
- 自检：写完每条结论后，回溯引用的事实卡片，确认确定性层级是否一致
→ 保存：04_推导过程.md
Step 6.5: 独立 Agent 校验（BLOCKING）
时机：事实卡片 + 推导过程完成后，写最终报告前。
原则：遵循 CLAUDE.md「计划校验」规范 — 产出者 ≠ 审查者。
执行方式：启动独立 Agent（Task 工具），将 02_事实卡片.md 和 04_推导过程.md 交给 Agent，校验以下维度：
- 数据准确性：关键数字（价格、版本号、参数规模等）做二次搜索验证，至少抽查 3-5 个核心数据点
- 推导逻辑：结论是否有跳跃、是否悄悄升级了确定性层级
- 遗漏检查：是否遗漏了用户关心的关键对比维度
→ 保存：05.5_校验记录.md
铁律：
- ❌ 不得跳过此步直接写最终报告
- ❌ 不得自己校验自己（必须启动独立 Agent）
- ✅ 校验通过 → 继续 Step 7-8；校验发现错误 → 回溯修正事实卡片/推导过程
Step 7: 用例验证（Sanity Check）
用一个典型场景验证结论是否成立，检查有无反例。
→ 保存：05_验证记录.md
Step 8: 可交付化处理
交付三件套：
- 一句话总结：可在会上直接复述
- 结构化章节：用小标题切开推导链
- 证据可追溯：关键事实附出处链接
→ 保存：FINAL_调研报告.md
→ 打包：tar -czvf ~/outcome.tar.gz -C ~/Downloads/research <topic>
报告输出结构
# [调研主题] 调研报告
## 摘要
[一句话核心结论]
## 1. 概念对齐
## 2. 工作机制
## 3. 联系
## 4. 区别
## 5. 用例演示
## 6. 总结与建议
## 参考资料详见 templates/report-structure.md
质量检查清单
Show full SKILL.md (198 more words)Show less
🎯 边界守恒检查（BLOCKING - 防止调研蔓延）
核心问题：调研最容易出的问题不是「查得不够多」，而是「查得太散」。
检查流程：
回顾核心问题：Step 1 拆解的子问题是什么？用一句话写下来。
资料相关性审计：对
01_资料来源.md中的每条资料，用以下结构化标准判断：- 「这条资料能回答哪个子问题？」→ 写出对应的子问题编号
- 如果无法对应任何子问题 → 删除，不要心疼
- 如果「有点关系但不直接」→ 降级为补充材料，不进入主报告
- ★ 高风险调研（涉及政策、医疗、法律等）：建议使用 Task 工具启动独立 Agent 复核相关性判断（产出者 ≠ 审查者）
事实卡片瘦身：对
02_事实卡片.md中的每张卡片问：- 「删掉这张卡片，核心结论还能成立吗？」
- 如果能 → 这张卡片是认知负担，移到附录或删除
报告聚焦检验：最终报告中的每个章节都要能追溯到 Step 1 的子问题
典型症状：
| 症状 | 表现 | 问题 |
|---|---|---|
| 边界蔓延 | 调研 A，顺便查了 B、C、D | 报告臃肿，重点模糊 |
| 资料囤积 | 收集 50 条资料，只用了 10 条 | 浪费时间，增加噪音 |
| 概念发散 | 解释一个概念时引入 3 个新概念 | 读者认知过载 |
| 炫技式延伸 | 「其实还有更深层的机制……」 | 偏离用户实际需求 |
铁律：调研的目标是回答问题，不是展示知识面。
核心检查
- 所有核心结论都有 L1/L2 级别的事实支撑
- 对比维度完整，没有遗漏关键差异
- 有至少一个实际用例验证结论
- 参考资料完整，链接可访问
- 每个引用都可被用户直接验证
- 一句话总结清晰可复述
时效性检查（🔴🟠 敏感领域 BLOCKING）
- 资料时效性已标注
- 版本号已明确标注
- 官方源已优先使用
- 下载页面已直接验证
- 协议/功能名称已搜索
- GitHub Issues 已挖掘
适用对象一致性检查（BLOCKING）
- 研究边界已明确定义
- 每条资料都标注了适用对象
- 事实卡片中无对象混淆
- 报告中无对象混淆
执行范围与理论风险区分检查（BLOCKING）
核心问题：调研涉及封禁、限制、政策执行等「行动」时，最容易犯的错误是把理论风险等同于实际后果。
错误模式：
- 事实卡片 A 正确记录了「只有 Gemini 被禁用」（确认的实际后果）
- 事实卡片 B 正确记录了「OAuth token 理论上可访问 Gmail/Drive」（安全理由/理论风险）
- 推导过程把 B 的理论范围 → 等同于 A 的执行范围
- 最终报告写成「整个账户生态受影响」← 这是偷换
三层区分（事实卡片和报告中必须明确标注）：
| 层级 | 含义 | 标注格式 | 示例 |
|---|---|---|---|
| 已确认 | 一手用户报告证实发生了 | [已确认] | "Gemini 服务被禁用" |
| 官方理由 | 执行方的解释/动机 | [官方理由] | "OAuth token 可能被滥用于访问更广的 Google 服务" |
| 理论风险 | 技术上可能但未被用户报告证实 | [理论风险] | "Gmail、Drive 等服务可能受牵连" |
检查清单：
- 涉及封禁/限制/执行动作时，事实卡片是否区分了三层？
- 推导过程中，是否有从「理论风险」直接跳到「已确认后果」的逻辑跳跃？
- 最终报告中，执行动作的描述是否严格基于「已确认」层级？
- 「官方理由」和「理论风险」是否作为分析/解释出现，而非作为已发生的事实？
铁律：「X 在技术上可能发生」≠「X 已经发生」。报告中描述执行后果时，只能使用「已确认」层级的事实。「理论风险」可以作为分析维度呈现，但必须明确标注，不得混入事实性陈述。
典型事故：调研报告说「整个 Google 账户生态可能受影响」（基于 OAuth 理论范围），文章据此写「Gmail、Drive、Cloud 都受牵连——你的数字生活被掐断」。实际上用户报告只有 Gemini/Antigravity 被禁用，Gmail/Drive 完全不受影响。读者亲历者指出错误，作者声誉受损。
来源周全性要求
- URL 可访问性：所有链接公开可访问
- 引用精确定位：标明具体章节/页码
- 内容对应性：引用能在原文找到对应
- 时效性标注：标注发布/更新日期
- 不可验证信息：标注
[来源受限]，不作为唯一支撑
最终回复规范
✅ 应该包含：
- 一句话核心结论
- 关键发现摘要（3-5 点）
- 打包文件位置（
~/outcome.tar.gz）
❌ 禁止包含：
- 过程文件列表
- 详细调研步骤
- 工作目录结构
版本历史
| 版本 | 变更 |
|---|---|
| v2.1.0 | 新增 Step 6.5：独立 Agent 校验（BLOCKING），写报告前必须校验事实和推导 |
| v2.0.0 | 重构：模板外移到 templates/，SKILL.md 精简 |
| v1.6 | 社区声音挖掘机制 |
| v1.5 | 官方下载页面验证、协议名称搜索 |
| v1.4 | 时效敏感性判断机制 |
| v1.3 | 来源周全性要求 |
| v1.2 | 适用对象核查机制 |
| v1.1 | 中间产物管理 |
| v1.0 | 初始版本 |
© nexu-io, MIT. 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 4 other files in apps/desktop/static/bundled-skills/deep-research of nexu-io/nexu.
- SKILL.md
- templates/comparison-framework.md
- templates/fact-card.md
- templates/intermediate-outputs.md
- templates/report-structure.md
Open the folder on GitHubat commit dadfb1c
Compare with similar skills
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|---|---|---|---|---|---|---|
| Deep Research this skillnexu-io/nexu | 3.3k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Use Avibeavibe-bot/avibe | 622 | — | ~2.5k | Automated safety check: Pass | MIT | |
| Wechat Article Writerstaruhub/ClaudeSkills | 727 | — | ~1.8k | Automated safety check: Pass | MIT | |
| Wechat Article Searchinfometa/workbuddyskills | 346 | — | ~479 | Automated safety check: Pass | None | |
| Claude To Imop7418/Claude-to-IM-skill | 2.9k | — | ~3.4k | Automated safety check: Notes | MIT | |
| Content CollectorvigorX777/content-collector-skill | 240 | — | ~2k | Automated safety check: Pass | None |
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Related
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Categories
Questions about Deep Research
What does Deep Research do?
深度调研方法论（8步法）：将模糊主题转化为高质量调研报告. An agent skill from nexu-io/nexu. Deep Research is an agent skill from nexu-io/nexu.
When should I use Deep Research?
Deep Research fits situations like: tasks that involve Deep research; tasks that involve Messaging and chat bots.
How do I install Deep Research in Claude Code?
Run `npx skills add nexu-io/nexu --skill deep-research -a claude-code`. Or copy the skill folder (apps/desktop/static/bundled-skills/deep-research in nexu-io/nexu) into .claude/skills/deep-research in your project. Claude Code loads it when a task matches its description.
How do I install Deep Research in Codex?
Run `npx skills add nexu-io/nexu --skill deep-research -a codex`. Or copy the skill folder (apps/desktop/static/bundled-skills/deep-research in nexu-io/nexu) into .agents/skills/deep-research in your project. Codex loads it when a task matches its description.
Can I use Deep Research 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 nexu-io/nexu --skill deep-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deep-research, .gemini/skills/deep-research, .github/skills/deep-research and .opencode/skills/deep-research in your project.
What does Deep Research need to run?
SKILL.md names no scripts, command-line tools or credentials: Deep Research is instructions for the agent only.
Does Deep Research 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 Deep Research 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 Deep Research use?
Deep Research is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Deep Research use?
About 1.6k tokens (SKILL.md is roughly 6.4k 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 Deep Research?
Skills that share tags, products or a category with Deep Research: Use Avibe (avibe-bot/avibe, 622 stars), Wechat Article Writer (staruhub/ClaudeSkills, 727 stars), Wechat Article Search (infometa/workbuddyskills, 346 stars) and Claude To Im (op7418/Claude-to-IM-skill, 2.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Deep Research?
nexu-io (a GitHub organization) maintains it in nexu-io/nexu, which has 3,282 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on April 26, 2026.
Source: nexu-io/nexu on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.