Best fit
- Interview notes, usability-test observations, support tickets, sales call notes,
- A decision that needs evidence: "Should we build X?", "Which onboarding path
- A need to share findings with stakeholders who will not read a long research
nexu-io/open-design
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.
npx skills add https://github.com/nexu-io/open-design --skill "skills/research-decision-room"Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Reorganized from the pinned upstream SKILL.md
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 vi…
npx skills add https://github.com/nexu-io/open-design --skill "skills/research-decision-room"The pinned source contains enough sections and task detail for a source-grounded deep guide; automated content is still not an independent test.
672 source words · 10 usable sections
Best fit
Design process
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
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.
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.
Normalize every useful signal into ledger rows using the model in references/evidence-model.md.
Cluster evidence into 4 to 6 themes. For each theme:
Create an opportunity matrix with 3 to 5 options. Score each option on a 1 to 5 scale:
SkillSignal prompt templates
These prompts were written by SkillSignal from the source structure; they are not upstream text.
Source-grounded prompt
Use for a design task while explicitly checking the source sections.
Use research-decision-room for this design task: [task]. Inputs and constraints: [details]. Work through these pinned SKILL.md sections: “Workflow”, “Step 1 - Establish the decision frame”, “Step 2 - Build the evidence ledger”, “Step 3 - Synthesize themes and tensions”, “Step 4 - Score opportunities”. Cite the concrete requirements that shape each step, do not invent capabilities absent from the source, and verify the result against: [acceptance criteria].
Design checklist
The source section “Workflow” has been checked.
The source section “Step 1 - Establish the decision frame” has been checked.
The source section “Step 2 - Build the evidence ledger” has been checked.
The source section “Step 3 - Synthesize themes and tensions” has been checked.
Choose a different workflow
Use when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.
A separate implementation from event4u-app/agent-config; compare its source, maintenance signals, and permission requirements.
Open source detailAnalyze Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.
A separate implementation from K-Dense-AI/scientific-agent-skills; compare its source, maintenance signals, and permission requirements.
Open source detailFacilitates evidence-aware scientific ideation with independent generation, structured discussion, explicit assumptions, transparent evaluation, adversarial review, and decision logs. Use for early-stage research brainstorming or prioritizing candidate directions; hand off empirical validation, study design, ethics or regulatory review, and clinical questions to appropriate experts or skills.
A separate implementation from K-Dense-AI/scientific-agent-skills; compare its source, maintenance signals, and permission requirements.
Open source detailFAQ
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 vi…
The source record exposes this install command: npx skills add https://github.com/nexu-io/open-design --skill "skills/research-decision-room". Inspect the command and pinned source before running it.
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Compare before choosing
These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.
Use when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.
Analyze Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.
Facilitates evidence-aware scientific ideation with independent generation, structured discussion, explicit assumptions, transparent evaluation, adversarial review, and decision logs. Use for early-stage research brainstorming or prioritizing candidate directions; hand off empirical validation, study design, ethics or regulatory review, and clinical questions to appropriate experts or skills.
Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.
Two related workflows for a locally-cloned codebase, in one skill. Documentation mode produces a single, comprehensive, verifiable architecture document primarily by reading files on disk (local-first) — use it whenever the user wants to understand, map, document, research, or onboard onto a codebase ("research this repo", "write up the architecture", "do an architecture deep dive", "document how this codebase works", "map the system design", "create an onboarding doc"). Modernization mode gener
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.
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.
Use this skill when the user has any mix of:
Do not use it for pure visual inspiration, campaign ideation, or brand moodboards.
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:
If key context is missing and the task is not blocked, proceed with labelled assumptions instead of asking a broad question.
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.
Cluster evidence into 4 to 6 themes. For each theme:
Prefer verbs over nouns: "Teams abandon setup when the first blank state asks for too much" is better than "Onboarding problem".
Create an opportunity matrix with 3 to 5 options. Score each option on a 1 to 5 scale:
Show the total score, but do not let the score replace judgment. Add one sentence on why the top recommendation wins.
Write a decision memo with:
Keep the memo short enough to read in under one minute.
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:
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.
Run the checklist. Then emit one concise orientation sentence and one HTML artifact:
<artifact identifier="research-decision-room" type="text/html" title="Research Decision Room">
<!doctype html>
<html>...</html>
</artifact>
Nothing after the closing </artifact>.