problem-solving▌
mrgoonie/claudekit-skills · updated Apr 8, 2026
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A collection of techniques for breaking through stuck points and finding elegant solutions.
Problem-Solving Skills
A collection of techniques for breaking through stuck points and finding elegant solutions.
Available Sub-Skills
When Stuck (Dispatch)
Location: when-stuck/SKILL.md
Start here when stuck. Matches your stuck-type to the right technique. Quick dispatch table for routing to the appropriate sub-skill.
Collision-Zone Thinking
Location: collision-zone-thinking/SKILL.md
Force unrelated concepts together to discover emergent properties. "What if we treated X like Y?" Revolutionary insights come from deliberate metaphor-mixing.
Inversion Exercise
Location: inversion-exercise/SKILL.md
Flip every assumption and see what still works. "What if the opposite were true?" Exposes hidden constraints and alternative approaches.
Meta-Pattern Recognition
Location: meta-pattern-recognition/SKILL.md
Spot patterns appearing in 3+ domains to find universal principles. Extract abstract forms that apply across domains.
Scale Game
Location: scale-game/SKILL.md
Test at extremes (1000x bigger/smaller) to expose fundamental truths. What breaks? What survives? Extremes reveal what normal scales hide.
Simplification Cascades
Location: simplification-cascades/SKILL.md
Find one insight that eliminates multiple components. "If this is true, we don't need X, Y, or Z." Look for unifying principles.
When to Use
| How You're Stuck | Use This |
|---|---|
| Don't know which technique | when-stuck |
| Need breakthrough innovation | collision-zone-thinking |
| Forced by assumptions | inversion-exercise |
| Same issue in different places | meta-pattern-recognition |
| Unsure about production scale | scale-game |
| Complexity spiraling | simplification-cascades |
Quick Reference
Conventional solutions inadequate? → collision-zone-thinking
"This must be done this way"? → inversion-exercise
Same pattern 3+ places? → meta-pattern-recognition
Will it work at scale? → scale-game
Same thing implemented 5+ ways? → simplification-cascades
Core Philosophy
"One powerful abstraction > ten clever hacks"
These techniques help you find the elegant solution that makes complexity unnecessary, rather than managing complexity through brute force.
How to use problem-solving 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 problem-solving
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches problem-solving from GitHub repository mrgoonie/claudekit-skills 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 problem-solving. Access the skill through slash commands (e.g., /problem-solving) 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
4.6★★★★★75 reviews- ★★★★★Dhruvi Jain· Dec 28, 2024
Registry listing for problem-solving matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Hassan Robinson· Dec 24, 2024
I recommend problem-solving for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Jin Mensah· Dec 20, 2024
problem-solving fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Maya Jain· Dec 16, 2024
problem-solving reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Maya Shah· Dec 16, 2024
Solid pick for teams standardizing on skills: problem-solving is focused, and the summary matches what you get after install.
- ★★★★★Zaid Menon· Dec 12, 2024
I recommend problem-solving for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Oshnikdeep· Nov 19, 2024
Solid pick for teams standardizing on skills: problem-solving is focused, and the summary matches what you get after install.
- ★★★★★Lucas Li· Nov 15, 2024
problem-solving fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Hassan Choi· Nov 15, 2024
Useful defaults in problem-solving — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Jin Kim· Nov 7, 2024
We added problem-solving from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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