research-decision-room
Transforms research notes into a clear document with evidence and decisions. It helps base product decisions on real data, avoiding guesswork.
What it does
Transforms research notes, interviews, and other data into a clear document that helps teams make evidence-backed decisions. It organizes information to facilitate debate and choosing the next step.
When to use it
- ✓When you have many interview notes or customer feedback and need to organize them.
- ✓When the team needs to make an important decision (e.g., which feature to build) based on real data.
- ✓When you need to present findings concisely to people who won't read long reports.
Example of what to ask your AI
“Organize my interview notes and support tickets about the login problem into a decision room, focusing on how to improve the user experience.”
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
Ready-to-paste message
How it works
The AI first understands what decision needs to be made. Then, it organizes all your notes into a structured list, identifies key themes, and evaluates options for the decision.
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 nexu-io/open-design --skill research-decision-roomOr download just the file:
curl -L https://raw.githubusercontent.com/nexu-io/open-design/main/skills/research-decision-room/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Research Decision Room Skill
Create a single-page HTML decision artifact that helps a product or design team turn messy evidence into a clear next move. The output is not a decorative research deck. It is a working room for debate: evidence, themes, confidence, tradeoffs, and recommended experiments stay visible together.
Resource map
research-decision-room/
├── SKILL.md
├── example.html
└── references/
├── checklist.md
└── evidence-model.md
Read references/evidence-model.md before synthesis and run
references/checklist.md before emitting the artifact.
When to use this skill
Use this skill when the user has any mix of:
- Interview notes, usability-test observations, support tickets, sales call notes, app-store reviews, NPS comments, survey open text, analytics snippets, or product-decision context.
- A decision that needs evidence: "Should we build X?", "Which onboarding path should we try?", "Why are users dropping off?", "What do customers actually mean by slow?"
- A need to share findings with stakeholders who will not read a long research report.
Do not use it for pure visual inspiration, campaign ideation, or brand moodboards.
Workflow
Step 1 - Establish the decision frame
Identify the decision scope from the user's prompt. If the user did not give a decision, derive one from the evidence and label it as inferred.
Write a short frame with:
- Decision question.
- Audience or segment.
- Time horizon.
- Known constraints.
- What this artifact will not decide.
If key context is missing and the task is not blocked, proceed with labelled assumptions instead of asking a broad question.
Step 2 - Build the evidence ledger
Normalize every useful signal into ledger rows using the model in
references/evidence-model.md.
Each ledger row must include:
id: short stable id, such asI-03,T-14,M-02.source_type: interview, usability, support, survey, analytics, sales, field note, or stakeholder.segment: user type or "unknown".signal: one-sentence observation.quote_or_metric: direct quote, metric, or "not provided".strength: strong, medium, or weak.limitations: why this evidence may be biased or incomplete.
Never invent quotes, participant counts, dates, revenue impact, or metrics. If the user did not provide a number, use "not provided" and explain what evidence would increase confidence.
Step 3 - Synthesize themes and tensions
Cluster evidence into 4 to 6 themes. For each theme:
- Name the theme in plain human language.
- List the evidence ids that support it.
- Explain the behavior behind it, not just the UI complaint.
- Mark confidence as high, medium, or low.
- Note contradictions or segment differences.
Prefer verbs over nouns: "Teams abandon setup when the first blank state asks for too much" is better than "Onboarding problem".
Step 4 - Score opportunities
Create an opportunity matrix with 3 to 5 options. Score each option on a 1 to 5 scale:
- Evidence strength.
- User pain.
- Business leverage.
- Implementation risk, where 5 means low risk and 1 means high risk.
Show the total score, but do not let the score replace judgment. Add one sentence on why the top recommendation wins.
Step 5 - Draft the decision memo
Write a decision memo with:
- Recommended move.
- Why now.
- What evidence supports it.
- What could be wrong.
- What to measure next.
- Reversible next step.
Keep the memo short enough to read in under one minute.
Step 6 - Create the HTML artifact
Produce a self-contained index.html. Use the active DESIGN.md for typography,
spacing, color roles, and component tone, but keep the information architecture
stable:
- Header with decision question, confidence, and last-updated label.
- Executive readout with recommendation, risk, and next experiment.
- Evidence ledger with filter chips.
- Theme map with evidence ids and confidence.
- Opportunity matrix.
- Decision memo.
- Experiment queue with owner, metric, and success threshold.
- Assumptions and limitations.
The artifact should be interactive but durable. Simple vanilla JavaScript is allowed for filtering evidence, switching views, or highlighting related ids. No framework dependency is required.
Step 7 - Self-check and emit
Run the checklist. Then emit one concise orientation sentence and one HTML artifact:
…
FAQ
What is a 'decision room'?
It's a single document that brings together all relevant information (evidence, themes, options) to help a team debate and make a clear decision, rather than just presenting data.
What is 'evidence' in this context?
It's the raw data you provide, such as interview snippets, usability test notes, support comments, survey results, etc.
Can I use this for creative ideation?
No, this tool focuses on turning existing data into concrete decisions, not on generating visual or campaign ideas from scratch.
Details
Original description by the author
Turn messy user research notes, interviews, support tickets, surveys, and product context into an evidence-backed decision room: a single HTML artifact with an evidence ledger, theme map, confidence heatmap, opportunity matrix, decision memo, and experiment queue. Use when teams need to move from qualitative signals to product or design decisions without fabricating certainty.
repo: nexu-io/open-design
Popularity
- GitHub stars
- 101k
- Ranking position
- #762
- License
- Apache-2.0
- Updated
- 10/16/2026
Comments
- …
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