ulw-research
适合需要深度证据链与多来源交叉验证的研究任务与技术尽调。
会运行代码并抓取外部资源，存在安全与数据泄露风险，需隔离执行环境。
高覆盖的研究编排器：并行探索代码库、网络与 OSS，带运行验证与引用合成报告。
做高覆盖、深度的研究编排：并行扫代码库、网络、官方文档和 OSS，甚至运行代码做实证验证，最后输出带引用的综合报告（可做 MD/HTML/PDF/PPTX）。只在你明确要求“做深度研究/ulw-research”时启动，适合需要彻底、可复现结论的场景。
▸ 展开 SKILL.md 英文原文
Maximum-saturation research orchestration: parallel explore+librarian swarms across codebase, web, official docs, and OSS repos; a recursive EXPAND loop driven by leads workers return in message text; empirical verification by running code; cited synthesis and optional MD/HTML/PDF/PPTX reports. ACTIVATES ONLY on an explicit user demand for research — the word 'ulw-research' ('/ulw-research', '$ulw-research'), any 'ulw' research wording, or an explicit request for research / deep research / an ultra-precise investigation, in any language. Never self-activates for ordinary questions, debugging, or implementation context-gathering. While active it overrides exploration-bounding defaults: exhaustive coverage is the goal.
帮我安装这个 skill：https://raw.githubusercontent.com/code-yeongyu/oh-my-openagent/dev/packages/shared-skills/skills/ulw-research/SKILL.mdcurl -fsSL "https://raw.githubusercontent.com/code-yeongyu/oh-my-openagent/dev/packages/shared-skills/skills/ulw-research/SKILL.md"## Codex Harness Tool Compatibility
This skill may include examples copied from the OpenCode harness. In Codex, do not call OpenCode-only tools such as `call_omo_agent(...)`, `task(...)`, `background_output(...)`, or `team_*(...)` literally. Translate those examples to Codex native tools:
| OpenCode example | Codex tool to use |
| --- | --- |
| `call_omo_agent(subagent_type="explore", ...)` | `multi_agent_v1.spawn_agent({"message":"TASK: act as an explorer. ...","agent_type":"explorer","fork_context":false})` |
| `call_omo_agent(subagent_type="librarian", ...)` | `multi_agent_v1.spawn_agent({"message":"TASK: act as a librarian. ...","agent_type":"librarian","fork_context":false})` |
| `tas