research-decision-room
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 qu
By nexu-io · 1,816 installs
npx skills add nexu-io/open-design --skill research-decision-room
Source repository · Upstream listing
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
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 as I 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:
1. Recommended move.
2. Why now.
3. What evidence supports it.
4. What could be wrong.
5. What to measure next.
6. 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:
1. Header with decision question, confidence, and last updated label.
2. Executive readout with recommendation, risk, and next experiment.
3. Evidence ledger with filter chips.
4. Theme map with evidence ids and confidence.
5. Opportunity matrix.
6. Decision memo.
7. Experiment queue with owner, metric, and success threshold.
8. 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:
Nothing after the closing </artifact .