ULW Research

by code-yeongyu

ULW Research is an AI Engineering skill for Claude Code, published by code-yeongyu in oh-my-openagent.

67.8K stars5.5K forkson code-yeongyu/oh-my-openagentAdded 2026/08/13Repository updated 2026/08/13

View source on GitHub Download repo ZIP

aiai-agentsanthropicchatgptclaudeclaude-skillscodexcursorgeminiideopenaiopencodeorchestrationtuitypescript

Install in seconds

Install ULW Research

Copy ULW Research into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/code-yeongyu/oh-my-openagent/tree/dev/packages/omo-senpi/skills/ulw-research ~/.claude/skills/ulw-research

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/code-yeongyu/oh-my-openagent.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: packages/omo-senpi/skills/ulw-research/SKILL.md in code-yeongyu/oh-my-openagent
Installs to: ~/.claude/skills/ulw-research
Collection: One of 21 skills cataloged from this repository
Category: AI Engineering — 2451 skills

What ULW Research does

ULW Research orchestrates a cooperating AI team for maximum-saturation research: it scopes axes, fans out to sources, runs debate rounds, proves contested claims with code, and delivers a cited synthesis with charts and assets. Activate it when an explicit, exhaustive research request is made.

ULW Research is cataloged under AI Engineering on DirSkills. ULW Research comes from a repository tagged ai, ai-agents, anthropic, chatgpt and claude.

Documentation

README

Excerpt

ULW-RESEARCH — Team-First Maximum-Saturation Research

You are the research orchestrator AND the team lead. The user has explicitly ordered exhaustive research: scope the topic, stand up a cooperating team, fan out over every relevant source, chase every lead until the leads run dry, attack your own findings through debate, prove contested claims by running code, and deliver a synthesis in which every claim carries a citation or a proof. Exhaustive coverage is the assignment, not a risk to manage.

Activation

This is the opening of the README. Read the full README on GitHub.

Commands ULW Research provides

Slash commands named in this skill’s SKILL.md, listed in the order they first appear.

/ulw-research

Frequently asked about ULW Research

What else does code-yeongyu publish alongside ULW Research?
ULW Research is one of 21 skills that DirSkills catalogs from code-yeongyu/oh-my-openagent, the repository it ships in. Its siblings there include Codex QA, Dead Code Removal and Get Unpublished Changes. Each one is a separate skill with its own page in this directory, installs the same way ULW Research does, and is maintained by code-yeongyu in that same repository. The rest of the collection is listed on the code-yeongyu/oh-my-openagent page.
How does ULW Research compare to other AI Engineering skills?
ULW Research ranks #79 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of ULW Research against them. Open each page to compare what they document and how they install.