Deep Product Research Prompt Generator

Deep product analysis tool.

Arguments: $ARGUMENTS

Instructions

Generate a comprehensive deep research prompt for the product question “$ARGUMENTS” tailored to the current project’s product context — its users, UI/UX patterns, domain, and existing design decisions.

If no topic is provided, ask the user what product question they want to research (e.g., onboarding flow, navigation patterns, empty states, pricing page, settings UX, notification design, search experience, mobile responsiveness).

Phase 1: Understand the Product

Analyze the current project to build a product profile. You’re looking for what this product IS, who it’s for, and what design decisions have already been made.

App Type & Domain

Determine what kind of product this is:

• Platform type: Web app, desktop app (Electron/Tauri), mobile app, CLI, browser extension, SaaS, marketplace, etc.
• Domain: E-commerce, developer tools, productivity, social, education, healthcare, finance, content/media, etc.
• Business model clues: Free/paid, subscription, freemium, marketplace fees (check for pricing pages, plan tiers, billing code)

Look in:

• README.md, CLAUDE.md, or any project docs
• Route/page files for feature scope
• Landing page or marketing copy if present
• Package name, descriptions in package.json / composer.json / Cargo.toml

User-Facing Features

Map the product surface by scanning routes, pages, and navigation:

Design System & UI Patterns

Identify the existing design language:

• Component library: shadcn/ui, Radix, Material UI, Ant Design, Headless UI, custom components
• CSS approach: Tailwind, CSS modules, styled-components, Sass
• Design tokens: Colors, spacing, typography (check theme files, CSS variables, tailwind config)
• Layout patterns: Sidebar + content, top nav, dashboard grid, wizard/stepper, split pane
• Interaction patterns: Modals vs. inline editing, toasts vs. banners, forms vs. command palettes
• Existing component inventory: What reusable UI components already exist

Look in:

• tailwind.config.* for design tokens
• components/ui/ or similar for component library
• Theme/design token files
• Storybook config if present

User Context

Piece together who uses this product:

• User roles: Check auth, permissions, middleware for distinct user types
• Onboarding: Is there a setup wizard, welcome screen, or tutorial?
• Collaboration: Multi-user? Teams? Sharing? Real-time?
• Data ownership: Personal data, team data, public data?

Phase 2: Confirm Product Profile with User

IMPORTANT: First output the detected product profile as a text message to the user. Do NOT put the profile details inside the AskUserQuestion tool.

Step 1: Display the profile as text output

Output a message like this (with actual detected values):

I detected the following product profile for this project:

**Product:**
- Desktop app (Tauri) — developer productivity tool
- Manages local development environments and processes

**Users:**
- Individual developers
- No collaboration/team features detected

**Key Features:**
- Process management dashboard
- Log viewer with search
- Project configuration
- System tray integration

**Design:**
- React + Tailwind CSS
- shadcn/ui component library
- Sidebar + content layout
- Dark mode support

**Maturity:**
- Active development, core features established
- No onboarding flow detected

Step 2: Then ask for confirmation

AFTER displaying the profile above, use the AskUserQuestion tool with a simple confirmation question:

• Question: “Does this product profile look correct?”
• Options: “Yes, looks correct” / “Need corrections”

Wait for user confirmation before proceeding. If the user provides corrections, incorporate them.

Phase 3: Generate the Deep Research Prompt

Once the profile is confirmed, generate a comprehensive research prompt. The prompt should be structured for a deep research tool (like Claude, Perplexity, or similar).

Prompt Template

Generate output in this format (replace placeholders with actual product details):

START OF GENERATED PROMPT

I’m building a product with the following profile:

Product:

• [App type, platform, domain]
• [Core purpose in one sentence]

Target Users:

• [Primary user types and their goals]
• [Technical sophistication level]
• [Usage context: work, personal, team, etc.]

Current Feature Set:

• [List key features/screens]

Design System:

• [Component library, CSS approach]
• [Layout patterns currently used]
• [Key interaction patterns]

Product Maturity:

• [Stage: early prototype, MVP, established product, etc.]
• [Notable gaps or areas under development]

I need comprehensive research on [TOPIC from $ARGUMENTS] — specifically product design best practices, UX patterns, and real-world examples for a product like mine.

Research Scope

1. UX Patterns & Best Practices

For [TOPIC] in products like mine, research:

• Established UX patterns used by successful products in this domain
• Interaction design best practices specific to [app type]
• Information architecture considerations for [TOPIC]
• Common UX mistakes products make with [TOPIC]
• Accessibility considerations for [TOPIC]

2. Real-World Examples & Inspiration

Find examples of [TOPIC] from:

• Direct competitors or products in the same domain
• Best-in-class examples from any domain that solved [TOPIC] well
• Before/after case studies showing how products improved [TOPIC]
• Note what makes each example effective or ineffective

For each example, describe:

• What the product does
• How they handle [TOPIC]
• What makes their approach work (or not)
• Screenshots or detailed descriptions if possible

3. User Psychology & Behavior

Research the human side of [TOPIC]:

• User expectations — what do users expect from [TOPIC] in this type of product?
• Mental models — how do users think about [TOPIC]?
• Decision fatigue and cognitive load — how does [TOPIC] affect user effort?
• Error recovery — what happens when things go wrong with [TOPIC]?
• Progressive disclosure — how much complexity to show upfront vs. on demand?

4. Product-Specific Considerations

Given my product profile, research:

• How [TOPIC] should work for [user type] specifically
• [App type]-specific constraints and opportunities for [TOPIC]
• How [TOPIC] interacts with my existing features
• Scale considerations — how should [TOPIC] work with 10 items vs. 1,000?

5. Measuring Success

Research how to know if [TOPIC] is working:

• Key metrics to track for [TOPIC] (engagement, completion rate, time-on-task, etc.)
• User signals that [TOPIC] is working well or poorly
• A/B testing opportunities for [TOPIC]
• Qualitative signals — what to listen for in user feedback

Requested Output Format

Please provide your findings organized as:

1. Executive Summary

   • Top 10 most important [TOPIC] decisions for a product like mine
   • Priority-ranked recommendations

2. Pattern Library

   • Proven UX patterns for [TOPIC] with descriptions
   • When to use each pattern
   • Tradeoffs between approaches

3. Real-World Examples

   • 5-10 examples from real products
   • What each does well and what could be improved
   • Applicability to my product

4. Design Recommendations

   • Specific recommendations for my product
   • Wireframe-level descriptions where helpful
   • Copy/microcopy suggestions where relevant
   • Component and layout suggestions that fit my design system

5. Edge Cases & Empty States

   • First-time user experience for [TOPIC]
   • Empty states, zero-data states
   • Error states and recovery flows
   • Power user vs. new user considerations
   • Extreme data scenarios (none, few, many, too many)

6. Anti-Patterns

   • What NOT to do with [TOPIC]
   • Common mistakes products make
   • Why they’re problematic for users

7. Implementation Priorities

   • What to build first (MVP of [TOPIC])
   • What to add later (nice-to-have enhancements)
   • What to skip entirely

8. Resources

   • Relevant articles, case studies, talks
   • Design system references
   • Tools for prototyping or testing [TOPIC]

END OF GENERATED PROMPT

Phase 4: Present the Output

Output the generated prompt as plain text that the user can easily copy.

Before the prompt, add:

Here’s your deep research prompt for “[TOPIC]” tailored to your product. Copy this and paste it into your preferred research tool:

After the prompt, add:

Tip: This prompt works well with Claude, ChatGPT, Perplexity, or similar AI research tools. For best results, use a tool that can search the web for current information and real product examples.

Topic-Specific Additions

Depending on the topic provided in $ARGUMENTS, emphasize different aspects:

If topic is about “onboarding” / “first-run” / “setup”:

• Emphasize time-to-value, activation metrics, progressive profiling
• Include wizard vs. contextual onboarding patterns, empty state design
• Request examples of great onboarding from similar product types

If topic is about “navigation” / “information architecture”:

• Emphasize wayfinding, discoverability, mental models
• Include sidebar vs. top nav vs. command palette patterns, breadcrumbs, search
• Request examples of navigation scaling from simple to complex

If topic is about “search” / “filtering” / “discovery”:

• Emphasize query patterns, faceted search, typeahead, result ranking
• Include empty results, suggested searches, filter UX, saved searches
• Request examples from data-heavy products in similar domains

If topic is about “settings” / “preferences” / “configuration”:

• Emphasize organization, discoverability, defaults, dangerous settings
• Include inline vs. dedicated settings page, search within settings, import/export
• Request examples of settings UX that scales well

If topic is about “notifications” / “alerts” / “messaging”:

• Emphasize notification fatigue, urgency levels, channel selection
• Include in-app vs. push vs. email, notification preferences, batching
• Request examples of notification systems users actually like

If topic is about “empty states” / “zero data”:

• Emphasize first-time experience, calls to action, placeholder content
• Include illustration vs. text, educational empty states, sample data
• Request examples of empty states that drive engagement

If topic is about “forms” / “data entry” / “input”:

• Emphasize validation UX, inline errors, progressive forms, autosave
• Include multi-step forms, conditional fields, smart defaults
• Request examples of complex forms that feel simple

If topic is about “tables” / “lists” / “data display”:

• Emphasize sorting, pagination vs. infinite scroll, bulk actions, column management
• Include responsive table patterns, inline editing, density controls
• Request examples of data-dense UIs that remain usable

If topic is about “dashboard” / “home” / “overview”:

• Emphasize information hierarchy, actionable vs. informational, customization
• Include widget patterns, activity feeds, status summaries, quick actions
• Request examples of dashboards that serve both new and power users

If topic is about “pricing” / “plans” / “billing”:

• Emphasize comparison clarity, plan differentiation, upgrade paths
• Include pricing psychology, trial experiences, plan change UX
• Request examples of pricing pages with high conversion rates

If topic is about “mobile” / “responsive” / “touch”:

• Emphasize touch targets, thumb zones, progressive enhancement
• Include responsive patterns, mobile-specific interactions, offline states
• Request examples of products that transition well between desktop and mobile

If topic is about “dark mode” / “theming”:

• Emphasize readability, color contrast, image handling, user preference
• Include system preference detection, smooth transitions, edge cases
• Request examples of products with excellent dark mode implementations

If topic is about “error handling” / “error states”:

• Emphasize error recovery, clear messaging, suggested actions
• Include form errors, page-level errors, network errors, permission errors
• Request examples of products with graceful error handling

If topic is about “collaboration” / “sharing” / “teams”:

• Emphasize permissions, real-time presence, conflict resolution
• Include sharing models, role management, activity feeds, mentions
• Request examples of collaboration UX from similar product types

Notes

• Always include the product’s actual features and user types — they matter for relevant research
• If you can’t determine something about the product, note it as “[unknown]” and ask the user
• The generated prompt should be self-contained and not require additional context
• Tailor the examples section to the actual product domain (don’t request generic examples)
• Focus on product/UX decisions, not technical implementation — the prompt should help someone make design decisions, not write code