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在 OpenClaw 中安装
/install openai-deep-research-skill
功能描述
Execute multi-step deep research with the OpenAI Responses API, including question decomposition, evidence gathering with web search, contradiction tracking,...
安全使用建议
This skill is mostly coherent for performing cited research with the OpenAI Responses API, but take these precautions before installing or running it:
- The SKILL.md and code require an OpenAI API key (OPENAI_API_KEY) even though the registry metadata did not declare it — do not supply sensitive org-wide keys unless you trust and have reviewed the code.
- The script allows setting OPENAI_BASE_URL (custom gateway). Only point this to endpoints you control or trust; a malicious gateway could capture prompts/responses or API keys if you pass them explicitly.
- Installation is local via pip installing the bundled requirements (openai package). Run in an isolated environment (virtualenv/container) if you want to limit system exposure.
- The tool writes output files to outputs/...; review produced artifacts for sensitive content before sharing them.
- If you need extra safety, run with --dry-run or --disable-web-search first, and inspect scripts/deep_research.py to confirm it behaves as you expect.
If you want higher assurance, ask the publisher to update registry metadata to declare OPENAI_API_KEY and OPENAI_BASE_URL, and request a short security note explaining whether the code ever transmits data to endpoints other than the Responses API and the optional web-search tool.
功能分析
Type: OpenClaw Skill
Name: openai-deep-research-skill
Version: 0.1.0
The skill implements a structured multi-step research workflow (Plan -> Research -> Synthesize) using the OpenAI Responses API. The core logic in `scripts/deep_research.py` is well-implemented, utilizing standard libraries and the official OpenAI SDK for evidence gathering and report generation. There are no signs of malicious behavior such as data exfiltration, unauthorized shell execution, or persistence; the script strictly manages research artifacts within a local output directory and communicates only with the configured OpenAI endpoint.
能力评估
Purpose & Capability
The name/description (deep research using the OpenAI Responses API) matches the included script and README: the tool decomposes questions, gathers evidence (optionally via a web-search tool) and writes audit artifacts. However, the registry metadata claims there are no required environment variables or primary credential while the SKILL.md and scripts explicitly require OPENAI_API_KEY (and optionally OPENAI_BASE_URL). This discrepancy is a proportionality/information-gap issue.
Instruction Scope
SKILL.md and the Python script restrict activity to research workflow: planning, calling the OpenAI Responses API, optional web-search tool usage, and writing local artifact files under outputs/. Instructions do not direct reading unrelated system files or harvesting environment variables beyond the API key/base URL. The workflow also provides a dry-run mode to avoid API calls.
Install Mechanism
There is no remote installer; the SKILL.md tells the user to pip install from the bundled scripts/requirements.txt which only lists the official openai package. No remote downloads or executables are fetched, and included code runs locally. This is low install risk.
Credentials
The tool legitimately needs an OpenAI API key, but the registry metadata failing to list OPENAI_API_KEY (and OPENAI_BASE_URL) is inconsistent and could mislead users about what secrets the skill will use. The script allows pointing the client to an arbitrary OPENAI_BASE_URL (a user-controlled gateway). That feature is reasonable for some deployments but also increases risk: if you pass a malicious base URL you could exfiltrate prompts/responses to an attacker. Require/declare OPENAI_API_KEY in metadata and be cautious where you set base URL.
Persistence & Privilege
always is false; the skill does not request forced inclusion or write global agent configuration. It writes run artifacts into an outputs/<timestamp>-<slug> directory under the working directory, which is expected for this purpose and not an escalation of privilege.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install openai-deep-research-skill - 安装完成后，直接呼叫该 Skill 的名称或使用
/openai-deep-research-skill触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v0.1.0
Initial publish
元数据
常见问题
OpenAI Deep Research Skill 是什么？
Execute multi-step deep research with the OpenAI Responses API, including question decomposition, evidence gathering with web search, contradiction tracking,... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 104 次。
如何安装 OpenAI Deep Research Skill？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install openai-deep-research-skill」即可一键安装，无需额外配置。
OpenAI Deep Research Skill 是免费的吗？
是的，OpenAI Deep Research Skill 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
OpenAI Deep Research Skill 支持哪些平台？
OpenAI Deep Research Skill 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 OpenAI Deep Research Skill？
由 Grus（@guanglechen）开发并维护，当前版本 v0.1.0。
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