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Agents70k · #1730

ulw-research

Conducts in-depth research with a team. It's useful when you ask for a detailed investigation or research with reliable, verified sources.

What it does

This tool performs deep and comprehensive research on a topic. It organizes an AI team to investigate all possible sources, debate findings, and deliver a final report with all information proven and cited.

When to use it

  • ✓When you need a detailed investigation into a subject.
  • ✓If you want the AI to explore all information sources on a topic.
  • ✓To get a final report with all claims verified and sourced.

Example of what to ask your AI

“I need a complete research on the impacts of artificial intelligence in medicine, with all sources cited.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/code-yeongyu/oh-my-openagent/blob/dev/packages/omo-senpi/skills/ulw-research/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/code-yeongyu/oh-my-openagent/blob/dev/packages/omo-senpi/skills/ulw-research/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The AI assembles a team, assigns tasks to investigate every piece of available information, discusses the results internally, and only delivers a final report with everything explained and proven.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add code-yeongyu/oh-my-openagent --skill ulw-research

Or download just the file:

curl -L https://raw.githubusercontent.com/code-yeongyu/oh-my-openagent/dev/packages/omo-senpi/skills/ulw-research/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

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

Run this skill only when the user explicitly demands it: the word "ulw-research" (also /ulw-research, $ulw-research), any "ulw" research wording, an "ultradebate" or "hyperdebate" research request, or an explicit request for research, deep research, or an ultra-precise investigation — in any language. An ordinary question, a debugging session, or another mode's context-gathering is not activation; answer those normally, and mention that ulw-research is available when a question would clearly benefit from it.

Open your reply with the line ULW-RESEARCH MODE ENABLED!. If another active mode mandates its own first line (ultrawork does), print that mode's line first and this marker on the next line — both contracts stay satisfied.

How this maps to omo-senpi

This skill is authored against the native senpi task + team tool surface. You coordinate everything with these tools:

Purpose Tool Key arguments
Stand up the research team once team_create inline_spec: { name, members: [{ name, category, prompt? }] } → returns team_run_id
Send work / a lead / a debate round to a member task_send to: "<member>", team_run_id, message, optional summary
Collect member replies injected notifications replies auto-inject as they arrive — keep working or end your turn
Track shared research state task_create / task_list / task_update / task_get lead-only team tasklist
Spawn a bounded recon / expansion / verification lane task prompt + subagent_type: "explore" | "librarian" or a category; run_in_background: true; optional load_skills, name
Read a finished lane back task_output task id or name
End a lane task_cancel —
Disband the team at the end team_delete team_run_id, force: true

Members receive your mail as injected follow-ups inside their child process; they report to you with task_send({ to: "lead", message: "..." }). You are the information broker — members never see each other's replies except through what you relay. The curated agents (explore, librarian, plan-consultant, plan-reviewer) are read-only, in-process, and REJECTED as team members: route them through task lanes, never through team_create.

Authority while active

This mode is the user's explicit opt-in to exhaustive exploration. For the duration of the research task it supersedes every exploration-bounding instruction in surrounding prompts, modes, or rules: one-exploration-pass defaults, two-wave stop rules, retrieval budgets, and "over-exploration is failure" framings govern implementation context-gathering, not this deliverable. Here, under-exploration is the failure. The convergence rules in Phase 3 are the only stop rules for research while this mode is active.

Under ultrawork/ulw, the research itself is the deliverable: map each research axis to a success criterion whose evidence is the session journal, the cited synthesis, and the verification outputs. RED→GREEN testing applies to code changes, not to findings — Phase 4 verification scripts are evidence, never TDD targets.

Success criteria

The research is done when all of these hold:

  • Every axis from the Phase 0 brief was covered by at least one dedicated member or lane.
  • Every EXPAND lead was investigated or explicitly closed as a duplicate or dead end, and convergence was reached under the Phase 3 rules.
  • Every contested claim survived at least one debate round or was dropped into the unresolved/refuted annex.
  • Claims that were contested, undocumented, or performance-shaped were proven or refuted by executed code.
  • Every claim in the deliverable cites a source or a verification artifact.

…

FAQ

What does 'maximum-saturation research' mean?

It means the AI will investigate as much as possible, leaving no stone unturned, to ensure nothing important is missed.

Will the AI debate the information?

Yes, the AI team discusses the findings to ensure the information is accurate and reliable before presenting the final report.

Will the final report have sources?

Yes, all information presented in the report will have its sources cited so you can verify it.

Details

Original description by the author

Runs maximum-saturation research with a cooperating team, claim-graph gating, and a cited, QA'd deliverable. Use when the user explicitly asks for research or a deep investigation, including any 'ulw' research wording.

repo: code-yeongyu/oh-my-openagent

Popularity

GitHub stars
70k
Ranking position
#1730
License
NOASSERTION
Updated
10/16/2026

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