teach-impeccable▌
pbakaus/impeccable · updated Apr 8, 2026
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One-time setup that gathers design context and persists it to your AI config file.
- ›Scans your codebase to discover existing design patterns, brand assets, tech stack, and design tokens before asking questions
- ›Asks targeted UX questions about users, brand personality, aesthetic preferences, and accessibility needs, skipping what's already clear from exploration
- ›Synthesizes findings into a Design Context markdown section saved to .impeccable.md in your project root for all future sessi
Gather design context for this project, then persist it for all future sessions.
Step 1: Explore the Codebase
Before asking questions, thoroughly scan the project to discover what you can:
- README and docs: Project purpose, target audience, any stated goals
- Package.json / config files: Tech stack, dependencies, existing design libraries
- Existing components: Current design patterns, spacing, typography in use
- Brand assets: Logos, favicons, color values already defined
- Design tokens / CSS variables: Existing color palettes, font stacks, spacing scales
- Any style guides or brand documentation
Note what you've learned and what remains unclear.
Step 2: Ask UX-Focused Questions
ask the user directly to clarify what you cannot infer. Focus only on what you couldn't infer from the codebase:
Users & Purpose
- Who uses this? What's their context when using it?
- What job are they trying to get done?
- What emotions should the interface evoke? (confidence, delight, calm, urgency, etc.)
Brand & Personality
- How would you describe the brand personality in 3 words?
- Any reference sites or apps that capture the right feel? What specifically about them?
- What should this explicitly NOT look like? Any anti-references?
Aesthetic Preferences
- Any strong preferences for visual direction? (minimal, bold, elegant, playful, technical, organic, etc.)
- Light mode, dark mode, or both?
- Any colors that must be used or avoided?
Accessibility & Inclusion
- Specific accessibility requirements? (WCAG level, known user needs)
- Considerations for reduced motion, color blindness, or other accommodations?
Skip questions where the answer is already clear from the codebase exploration.
Step 3: Write Design Context
Synthesize your findings and the user's answers into a ## Design Context section:
## Design Context
### Users
[Who they are, their context, the job to be done]
### Brand Personality
[Voice, tone, 3-word personality, emotional goals]
### Aesthetic Direction
[Visual tone, references, anti-references, theme]
### Design Principles
[3-5 principles derived from the conversation that should guide all design decisions]
Write this section to .impeccable.md in the project root. If the file already exists, update the Design Context section in place.
Then ask the user directly to clarify what you cannot infer. whether they'd also like the Design Context appended to .github/copilot-instructions.md. If yes, append or update the section there as well.
Confirm completion and summarize the key design principles that will now guide all future work.
How to use teach-impeccable on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add teach-impeccable
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches teach-impeccable from GitHub repository pbakaus/impeccable and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate teach-impeccable. Access the skill through slash commands (e.g., /teach-impeccable) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★59 reviews- ★★★★★Neel Sharma· Dec 24, 2024
I recommend teach-impeccable for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Soo Li· Dec 24, 2024
Keeps context tight: teach-impeccable is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Dev Singh· Dec 12, 2024
teach-impeccable has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Ama Yang· Dec 4, 2024
Useful defaults in teach-impeccable — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Soo Gonzalez· Nov 23, 2024
teach-impeccable is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Arya Sharma· Nov 19, 2024
Registry listing for teach-impeccable matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Dev Gupta· Nov 15, 2024
Keeps context tight: teach-impeccable is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Omar Farah· Nov 15, 2024
I recommend teach-impeccable for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Piyush G· Nov 7, 2024
Registry listing for teach-impeccable matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Arya Jain· Nov 3, 2024
teach-impeccable fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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