deep-research
Exa-powered deep research producing an evidence-backed findings.md report. Load for research tasks, architectural investigations, and vendor, library, or technology comparisons.
供给资产档案
编程与开发 Agent
代码审查、仓库分析、测试、CI、GitHub、DevOps 与开发工作流 Skill。
场景
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
适配 Agent
Claude Code + OpenAI Agents + Cursor
适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。
安装
就绪
npx skills add vanillagreencom/kendex --skill deep-research
维护状态
新鲜
今天有推送
风险
需审查
Quality score needs review
GitHub 质量
63
65/100 质量 · 76/100 信任
覆盖标签
审查说明
Quality score needs review · GitHub adoption: 63 GitHub stars
Agent 采用评分卡
一眼查看信任、审计与安装准备度
这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。
质量
有潜力有用的候选项,但采用前应与替代方案比较。
信任
仅限沙盒有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。
审计
需审查对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。
OpenAgentSkill 信任评分 v5
安装前需人工审查
仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。
Stars
63 个 GitHub Stars
仓库活跃度
63 个 Star,23 个 Fork
维护状态
今天有推送
许可证
MIT
安装
npx skills add vanillagreencom/kendex --skill deep-research
安装安全性
标准软件包或运行时安装路径
权限范围
shell or command execution, filesystem or document access
Agent 结果
暂未有 Agent 结果数据
文档
README/SKILL.md 上下文充分
风险摘要
生产前审查
- Quality score needs review
- GitHub adoption: 63 GitHub stars
- Stars/forks activity: 63 stars, 23 forks; issue activity unavailable in current metadata
安装准备度
安装路径可用
- 安装路径可用
- 仓库证据可用
- 已声明许可证
- 暂无 Agent 验证结果证据
Agent 可读元数据
这个 Skill 的机器可读决策数据。
使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。
适用任务
- 研究 Agent 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
- 检索来源
适用 Agent
安装决策
- 命令
- npx skills add vanillagreencom/kendex --skill deep-research
- 策略
- 审查
- 人工审查
- 是
信任与风险
- 信任
- 68/100
- 审计
- 79/100
- 风险级别
- 需审查
结果闭环
- 端点
- /api/agent/outcome
- 事件 ID
- resolve
- 结果
- 5
不适用场景
- 需要厂商支持 SLA 的团队
- 没有内部安全审查的高合规环境
- 当前元数据中未发现重大风险信号
- 高风险权限提示:Shell 或命令执行
- Quality score needs review
替代 Skill
Last30days Skill
53.5K Stars
npx skills add mvanhorn/last30days-skill -g
替代 Skill
Academic Research Skills
38.4K Stars
npx skills add Imbad0202/academic-research-skills
替代 Skill
GPT Researcher
28.0K Stars
npx skills add assafelovic/gpt-researcher
替代 Skill
DeepResearch
19.8K Stars
npx skills add Alibaba-NLP/DeepResearch
Agent 安全 v2
47/100 · 避免自动安装
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
高
Shell 或命令执行
Skill 元数据引用了终端、CLI、Shell、子进程或命令执行工作流。
中
网络访问
Skill 可能访问远程页面、API、仓库或外部服务。
中
文件系统访问
Skill 可能读取或写入项目文件、文档、生成产物或本地工作区状态。
中
数据库访问
Skill 可能检查 Schema、查询数据库或处理持久化存储。
- 高风险权限提示:Shell 或命令执行
- Quality score needs review
安装目标
在你的 Agent 工作流中安装此 Skill
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install vanillagreencom-deep-researchAgent 解析计划
让 Agent 在安装前验证匹配度。
Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。
打开 JSON
/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve 文本
/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
安装交接
/api/skills/vanillagreencom-deep-research/install
Agent 应检查
- 从 Resolve API 检查任务匹配与替代方案。
- 检查审计评分、信任评分和安全策略警告。
- 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。
复制提示词
Task: Use deep-research in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/vanillagreencom-deep-research/install
Install command: npx skills add vanillagreencom/kendex --skill deep-research
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent 交接
把安装路径交给 Agent,而不是再给一个目录页。
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
安装交接
/api/skills/vanillagreencom-deep-research/install
LLM 文本格式
/api/skills/vanillagreencom-deep-research/install?format=text
寻找替代方案
/api/skills/search?q=deep-research&limit=3
Agent 提示词
Use deep-research for this task. Review https://www.openagentskill.com/api/skills/vanillagreencom-deep-research/install, then install with: npx skills add vanillagreencom/kendex --skill deep-researchRegistry 元数据
用于自动选择 Skill 的 Agent 可读档案。
本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。
Agent 决策面板
Fallback candidate for Research agents
先用此 Skill 做原型验证,并保留备选方案。
栈中角色
备选候选
主要匹配
研究 Agent
信任标签
先做原型验证
安装路径
命令已就绪
适用场景
- 研究 Agent 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
证据
- 仓库近期活跃
- 已提供安装命令或 GitHub 仓库
- 65/100 质量档案
- 2 个 OpenAgentSkill 交互事件
先审查
- 当前元数据中未发现重大风险信号
实施路径
- 1在沙盒 Agent 中安装它,并端到端完成一次研究 Agent任务。
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
信任档案
仅限沙盒
有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。
GitHub 采用度
检查63 个 GitHub Stars
Star/Fork 活跃度
检查63 个 Star,23 个 Fork; 当前元数据中没有议题活跃度信息
近期维护
通过今天有推送
许可证清晰度
通过MIT
积极信号
- AI 审查已通过
- 安装路径可用
- 仓库证据可用
- 近期维护的仓库
- 安装命令未发现明显高风险模式
- 结果闭环已就绪,但需要首次真实 Agent 运行
安装前审查
- Quality score needs review
- GitHub adoption: 63 GitHub stars
- Stars/forks activity: 63 stars, 23 forks; issue activity unavailable in current metadata
- 暂未有真实 Agent 结果报告
- 无人值守安装前需要人工审查
建议操作
仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。
质量档案
有潜力 适用于 Agent 工作流的候选
有用的候选项,但采用前应与替代方案比较。
工作流匹配
在这些场景使用此 Skill
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Build and ship code
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
工作流匹配
加入完整工作流
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Turn skills into distribution
Content growth agent
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
替代方案短名单
安装前对比
可能适合该任务的相近 Skill。
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
概览
--- name: deep-research description: "Exa-powered deep research producing an evidence-backed findings.md report. Load for research tasks, architectural investigations, and vendor, library, or technology comparisons." license: MIT user-invocable: true argument-hint: "report [query] --output findings.md" dependencies: optional: [decider] metadata: author: vanillagreen source: kendex repository: "https://github.com/vanillagreencom/kendex" bugs: "https://github.com/vanillagreencom/kendex/issues" version: "1.1.0" tags: [research] ---
# Deep Research
> **Problem with this skill?** Run `kendex report` — it files to the owning repo automatically. Do not hand-file.
Evidence-backed research reports: architectural investigations, vendor and library comparisons, technology choices, and workflow-owned `findings.md` reports.
In Pi with the `web_research` tool active, use that tool, passing `outputPath` when creating a report. In every other harness — Pi without it, Claude Code, Codex, OpenCode, Cursor — run `scripts/deep-research` with `EXA_API_KEY` set.
## Rules
- Exa is the research source. Substitute a general web search only when Exa is unavailable and the user approves the fallback. - Write `findings.md` to the path the caller requested, exactly. - Cite sources for material claims, and keep `findings.md` human-readable: provider payloads live in the sidecar JSON (`findings.raw.json` beside the report by default), never inline. Sanitize evidence excerpts so headings from source pages do not render as headings. - Once the report and its sidecar exist, run `validate` and stop. Do not add local reproduction, benchmarks, tests, code inspection, or implementation unless the caller asked for local validation on top of the research. - A missing `EXA_API_KEY` fails with setup instructions. The value may be a key or a 1Password `op://vault/item/field` reference when the `op` CLI is installed and signed in. - One findings format serves every mode: the mode changes depth and source volume, not the required sections. Record mode and source counts in `## Research Metadata`.
## Running
```bash skills/deep-research/scripts/deep-research report "question" --mode standard --output path/to/findings.md skills/deep-research/scripts/deep-research report --query-file prompt.txt --context-glob 'context-*.md' --mode full --output findings.md skills/deep-research/scripts/deep-research json "question" --output raw.json skills/deep-research/scripts/deep-research validate findings.md findings.raw.json skills/deep-research/scripts/deep-research doctor ```
`deep-research help` lists every flag. Exa `/search` caps the settings behind them: `numResults` 1-100, `text.maxCharacters` 1-10000, `additionalQueries` at most 10.
| Mode | Exa type | Results | Text cap | Timeout | Synthesis | |---|---|---:|---:|---:|---| | `lite` | `deep-lite` | 15 | 10k chars/result | 5 min | Not requested — evidence brief only | | `standard` | `deep-reasoning` | 50 | 10k chars/result | 10 min | Requested via `outputSchema` | | `full` | `deep-reasoning` | 100 | 10k chars/result | 30 min | Requested, per query |
`standard` is the default; `lite` suits fast spikes, `full` strategic or high-risk decisions. Explicit `--type`, `--num-results`, and `--text-max-characters` override a mode's defaults.
`--additional-query` (repeatable) reaches Exa as `additionalQueries` within the single request under `lite` and `standard`, and as one request per query with URLs deduped across responses under `full`; the sidecar records which, as `provider-additional-queries` or `local-fan-out`.
`--include-domain` is a hard host filter, not a quality filter: `--include-domain github.com` admits every repo on it and excludes everything else. Name authoritative projects and organizations in the query text when quality is what you want, and audit the returned source list either way.
## Validation
```bash skills/deep-research/scripts/deep-research validate path/to/findings.md path/to/findings.raw.json ```
Prints `{ok, errors, warnings, mode, synthesis, queryCount}` and exits 0 when there are no errors. It checks structure: required sections present, sidecar parses, query-expansion metadata self-consistent, and a synthesized answer present for the modes that requested one.
It cannot judge content. Read for these yourself:
- Claims the cited sources contradict — spot-check material numbers (complexity classes, benchmark results) against the source text in the sidecar. - Off-topic sources that share an acronym or name with the subject. - Recommendations with no claim-level support in Evidence and Sources. - Results generalized past what the source established.
## Findings format
`templates/findings.md` carries exactly the sections `validate` requires, in order. `Key Findings` holds distinct claims, not a restatement of the summary.
技术详情
- 版本
- 1.0.0
- 许可证
- MIT
- 最近更新
- 2026年8月23日
- 发布时间
- 2026年8月23日
决策摘要
备选候选
仓库近期活跃
Agent 验证证据
Agent 验证证据
来自解析、审查、安装和一次小范围运行后的结果报告。
- 成功率
- —
- 近期失败
- —
- 结果
- 0
- 输出质量
- —
- 失败
- 0
- 不相关
- 0
- 安装次数
- 0
- 风险拦截
- 0
- 需要配置
- 0
- 生产环境
- 0
暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。
增长闭环
分享工具包
为 deep-research 准备的场景化草稿,可手动发布到 X。
deep-research: Exa-powered deep research producing an evidence-backed findings.md report. Load for research... 63 stars https://www.openagentskill.com/skills/vanillagreencom-deep-research?ref=x
可选:带安装命令的回复
Listing + install path for deep-research: https://www.openagentskill.com/skills/vanillagreencom-deep-research?ref=x Install: npx skills add vanillagreencom/kendex --skill deep-research
收录来源
Registry 收录
此列表来自公开来源,维护者认领获批前不会标记为官方。
- 收录方
- OpenAgentSkill 社区索引
归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。
认领此 Skill所有者认领
认领此 Skill 页面
这条 Registry 收录 列表归属于 vanillagreencom,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。
创作者外链工具包
将证据徽章加入你的 README
在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。
[](https://www.openagentskill.com/skills/vanillagreencom-deep-research)
[](https://www.openagentskill.com/skills/vanillagreencom-deep-research)
[](https://www.openagentskill.com/skills/vanillagreencom-deep-research/audit)
[](https://www.openagentskill.com/skills/vanillagreencom-deep-research)作者
vanillagreencom
@vanillagreencom
健康信号
- GitHub Stars
- 63
- 质量评分
- 36/100
- 最近 GitHub 推送
- 2026年8月23日
- 框架提示
- 未知
- OpenAgentSkill 浏览量
- 2
- 复制安装命令
- 0
- 跳转点击
- 0
社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。
信任与安全
仅限沙盒
- GitHub 采用度63 个 GitHub Stars检查
- Star/Fork 活跃度63 个 Star,23 个 Fork; 当前元数据中没有议题活跃度信息检查
- 近期维护今天有推送通过
- 许可证清晰度MIT通过
- README/SKILL.md 完整度元数据包含足够的用法与工作流上下文通过
- 依赖与运行时风险命令执行范围信息
相关 Skill
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
53.5K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsDeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
19.8K Stars