Deep Research
XiaomiMiMo/MiMo-Code
Runs a multi-source investigation with parallel sub-agents and built-in web tools, then writes one cited report. Meant for open-ended topics, not quick lookups.
Runs an exhaustive, team-based research session that stands up cooperating agents, debates findings and delivers a report where every claim has a citation or proof.
Install ULW Deep Research
$ npx skills add code-yeongyu/oh-my-openagent --skill ulw-research -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install code-yeongyu/oh-my-openagent ulw-research --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/code-yeongyu/oh-my-openagent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/omo-senpi/skills/ulw-research .claude/skills/ulw-research && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ulw-research" agent skill from https://github.com/code-yeongyu/oh-my-openagent/tree/dev/packages/omo-senpi/skills/ulw-research into .claude/skills/ulw-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ulw-research", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/code-yeongyu/oh-my-openagent/tree/dev/packages/omo-senpi/skills/ulw-researchType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add code-yeongyu/oh-my-openagent --skill ulw-research -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install code-yeongyu/oh-my-openagent ulw-research --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/code-yeongyu/oh-my-openagent.git skills-src && mkdir -p .agents/skills && cp -r skills-src/packages/omo-senpi/skills/ulw-research .agents/skills/ulw-research && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ulw-research" agent skill from https://github.com/code-yeongyu/oh-my-openagent/tree/dev/packages/omo-senpi/skills/ulw-research into .agents/skills/ulw-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ulw-research", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add code-yeongyu/oh-my-openagent --skill ulw-research -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install code-yeongyu/oh-my-openagent ulw-research --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/code-yeongyu/oh-my-openagent.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/packages/omo-senpi/skills/ulw-research .cursor/skills/ulw-research && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ulw-research" agent skill from https://github.com/code-yeongyu/oh-my-openagent/tree/dev/packages/omo-senpi/skills/ulw-research into .cursor/skills/ulw-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ulw-research", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/code-yeongyu/oh-my-openagent.git --path packages/omo-senpi/skills/ulw-research--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add code-yeongyu/oh-my-openagent --skill ulw-research -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install code-yeongyu/oh-my-openagent ulw-research --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/code-yeongyu/oh-my-openagent.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/packages/omo-senpi/skills/ulw-research .gemini/skills/ulw-research && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ulw-research" agent skill from https://github.com/code-yeongyu/oh-my-openagent/tree/dev/packages/omo-senpi/skills/ulw-research into .gemini/skills/ulw-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ulw-research", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install code-yeongyu/oh-my-openagent ulw-researchInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add code-yeongyu/oh-my-openagent --skill ulw-research -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/code-yeongyu/oh-my-openagent.git skills-src && mkdir -p .github/skills && cp -r skills-src/packages/omo-senpi/skills/ulw-research .github/skills/ulw-research && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ulw-research" agent skill from https://github.com/code-yeongyu/oh-my-openagent/tree/dev/packages/omo-senpi/skills/ulw-research into .github/skills/ulw-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ulw-research", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add code-yeongyu/oh-my-openagent --skill ulw-research -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install code-yeongyu/oh-my-openagent ulw-research --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/code-yeongyu/oh-my-openagent.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/packages/omo-senpi/skills/ulw-research .opencode/skills/ulw-research && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ulw-research" agent skill from https://github.com/code-yeongyu/oh-my-openagent/tree/dev/packages/omo-senpi/skills/ulw-research into .opencode/skills/ulw-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ulw-research", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
ulw-research- GitHub stars
- 70k
- Token cost
- ~14k tokens
- SKILL.md length
- 7,560 words
- Files
- 3 (incl. references)
- Skills in repo
- 44
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Runs an exhaustive, team-based research session that stands up cooperating agents, debates findings and delivers a report where every claim has a citation or proof.
- Works in 7 steps: Scope solo, organize the brief → Stand up the team (DEFAULT composition) → Saturation wave → …
- Commissioning a thorough, cited investigation of a technical or factual topic
- SKILL.md covers Activation, How this maps to omo-senpi, Authority while active and Success criteria, plus 11 more sections
- Calls node, uv and git
What it does
Research is organized as a team effort. The agent scopes the topic, creates a research team with team_create, fans out across relevant sources through background explore and librarian lanes, and keeps chasing leads until they run dry. Findings are challenged through debate rounds, contested claims are tested by running code, and the final synthesis ties each claim to a citation or a proof.
It activates only on an explicit request: the ulw-research name, other ulw research wording, an ultradebate or hyperdebate request, or a plain ask for deep research, in any language. Ordinary questions and debugging sessions do not trigger it. Once active it opens its reply with a fixed mode banner line, tracks shared state in a lead-only task list and disbands the team at the end. A bundled reference file named latex-report.md accompanies it.
It is authored for the omo-senpi task and team tools, so it relies on calls such as team_create, task_send and task_output being available in your agent environment.
When your agent uses it
- Commissioning a thorough, cited investigation of a technical or factual topic
- Settling a contested claim by having agents debate it and test it in code
- Producing a research deliverable where each statement needs a source
Example prompts
- “Use ulw-research to look into how current vector databases handle filtered search, with citations.”
- “I need deep research comparing the main approaches to offline-first sync, and challenge your own conclusions.”
- “Investigate why our build times grew this quarter, and prove any claim you make by running code.”
Requirements
- An omo-senpi environment with the team_create, task_send and task tools
Workflow steps
7 steps, taken from the step headings in SKILL.md.
- Scope solo, organize the brief
- Stand up the team (DEFAULT composition)
- Saturation wave
- Expand and debate until convergence
- Verify contested claims by running code
- Synthesize
- Final materials, then teardown
What it can do on your machine
Read from SKILL.md and the folder at commit cbd7dd2. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
nodeuvgitghpandoc
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use uv, git and gh, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
ULW Deep Research loads about 14k tokens when it runs, and up to ~17k if it reads all its reference files. Until then it costs about 58 tokens; SKILL.md has 7,560 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 7,560 words (~14,010 tokens).
“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…”
- name
- ulw-research
- argument-hint
- <research-topic>
- metadata.short-description
- Team-default saturation research with debate cross-critique and cited synthesis
Files
SKILL.md and 2 other files (references) in packages/omo-senpi/skills/ulw-research of code-yeongyu/oh-my-openagent.
- SKILL.md
- ATTRIBUTION.md
- references/latex-report.md
Open the folder on GitHubat commit cbd7dd2
Used in 1 other repository
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders. This page covers the copy in code-yeongyu/oh-my-openagent, which our catalogue first saw on October 7, 2026.
Compare with similar skills
ULW Deep Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| ULW Deep Research this skillcode-yeongyu/oh-my-openagent | 70k | — | ~14k | Automated safety check: Pass | Custom licence | |
| Deep ResearchXiaomiMiMo/MiMo-Code | 14k | — | ~1.2k | Automated safety check: Pass | MIT | |
| Deep Research Teammalob/nix-config | 463 | 1 repos | ~5.8k | Automated safety check: Pass | MIT | |
| Advanced Swarm Orchestrationruvnet/agentic-flow | 816 | 5 repos | ~5.9k | Automated safety check: Pass | None | |
| Web ResearchJuncai22/spring-ai-agent-learning | 123 | 3 repos | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Deep Research312362115/claude | 107 | — | ~6.6k | Automated safety check: Pass | MIT |
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Patterns for running multi-agent swarms on research, development and testing work, with four topologies and a four-phase research swarm built on claude-flow MCP tools.
Web Research
Juncai22/spring-ai-agent-learning
A skill your agent uses for requests related to web research; it provides a structured approach to conducting comprehensive web research
Deep Research
312362115/claude
深度调研技能：对任意命题进行系统性调研并输出专业研究报告. An agent skill from 312362115/claude.
Deep Dive
rohitg00/awesome-claude-code-toolkit
Claude-native deep research using DAG-based query planning, parallel subagent execution, and gap-driven iteration.
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Related
Categories
Questions about ULW Deep Research
What does ULW Deep Research do?
Runs an exhaustive, team-based research session that stands up cooperating agents, debates findings and delivers a report where every claim has a citation or proof. Research is organized as a team effort. The agent scopes the topic, creates a research team with team_create, fans out across relevant sources through background explore and librarian lanes, and keeps chasing leads until they run dry.
When should I use ULW Deep Research?
ULW Deep Research fits situations like: commissioning a thorough, cited investigation of a technical or factual topic; settling a contested claim by having agents debate it and test it in code; producing a research deliverable where each statement needs a source.
How do I install ULW Deep Research in Claude Code?
Run `npx skills add code-yeongyu/oh-my-openagent --skill ulw-research -a claude-code`. Or copy the skill folder (packages/omo-senpi/skills/ulw-research in code-yeongyu/oh-my-openagent) into .claude/skills/ulw-research in your project. Claude Code loads it when a task matches its description.
How do I install ULW Deep Research in Codex?
Run `npx skills add code-yeongyu/oh-my-openagent --skill ulw-research -a codex`. Or copy the skill folder (packages/omo-senpi/skills/ulw-research in code-yeongyu/oh-my-openagent) into .agents/skills/ulw-research in your project. Codex loads it when a task matches its description.
Can I use ULW Deep Research in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add code-yeongyu/oh-my-openagent --skill ulw-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ulw-research, .gemini/skills/ulw-research, .github/skills/ulw-research and .opencode/skills/ulw-research in your project.
What does ULW Deep Research need to run?
Going by SKILL.md and its folder, ULW Deep Research needs the command-line tools its instructions call (node, uv, git, gh and pandoc). Our summary lists: An omo-senpi environment with the team_create, task_send and task tools.
Does ULW Deep Research access the network?
SKILL.md contains no URLs. Its commands use uv, git and gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is ULW Deep Research safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does ULW Deep Research use?
ULW Deep Research has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does ULW Deep Research use?
About 14k tokens (SKILL.md is roughly 56k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3k tokens, read only when the agent opens those files.
What are the alternatives to ULW Deep Research?
Skills that share tags, products or a category with ULW Deep Research: Deep Research (XiaomiMiMo/MiMo-Code, 14k stars), Deep Research Team (malob/nix-config, 463 stars), Advanced Swarm Orchestration (ruvnet/agentic-flow, 816 stars) and Web Research (Juncai22/spring-ai-agent-learning, 123 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains ULW Deep Research?
code-yeongyu (a GitHub user) maintains it in code-yeongyu/oh-my-openagent, which has 69,850 GitHub stars. The repository holds 44 skills in this directory. The repository was last updated on October 7, 2026.
Source: code-yeongyu/oh-my-openagent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.