📦 Deep — 深度
v1.0.0研究 使用并行子代理和迭代搜索进行深度多阶段研究。适用于深度研究请求、全面分析、竞争情报……
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by 下载技能包
最后更新
2026/4/21
安全扫描
OpenClaw
安全
high confidenceThe skill's instructions, requirements, and foothold are internally consistent with a deep-research assistant: it only contains orchestration instructions to spawn subagents and use search/fetch tools and requests no credentials or installs.
评估建议
This skill appears to do what it says: orchestrate parallel subagents to perform deep web research. Before installing, consider operational and policy implications: the workflow calls for fetching a large number of full articles (potentially from paywalled or copyrighted sources) and spawning multiple parallel subagents, which can increase API usage, generate rate-limit errors, or violate source terms of service. Confirm that your platform's web_fetch respects robots.txt and paywalls, and that y...详细分析 ▾
✓ 用途与能力
Name/description match the content of SKILL.md. The skill's requests (spawn subagents, run web_search and web_fetch, synthesize findings) are coherent with a multi-phase deep research workflow. No unrelated binaries, env vars, or config paths are requested.
ℹ 指令范围
Instructions explicitly direct spawning 6–10 subagents and fetching many sources (20–30 minimum, 5–10 full articles per subagent). This is consistent with 'deep research' but grants the agent broad discretion to perform heavy web crawling and content extraction. There are potential operational/privacy considerations (rate limits, copyright/paywall scraping, volume of data retrieved), but no instructions to access local files or unrelated credentials.
✓ 安装机制
No install spec and no code files — instruction-only. Nothing is downloaded or written to disk by the skill itself, which minimizes installation risk.
✓ 凭证需求
The skill requires no environment variables, credentials, or config paths. There is no disproportionate request for secrets or unrelated tokens.
✓ 持久化与权限
always:false and default autonomous invocation are used. The skill does not request permanent presence or modify other skills. Autonomous use combined with heavy external fetching is notable operationally but not a privilege escalation.
安全有层次，运行前请审查代码。
运行时依赖
无特殊依赖
版本
latestv1.0.02026/4/21
Initial release - parallel subagent research methodology
● 无害
安装命令
点击复制官方npx clawhub@latest install autosolutions-deep-research
镜像加速npx clawhub@latest install autosolutions-deep-research --registry https://cn.longxiaskill.com