Structured dialogue tool for collaboratively designing features, APIs, and architecture through phased information gathering and validation.
Works with
Guides through six phases: context discovery, requirements gathering, approach exploration, design presentation, documentation, and execution handoff
Uses batched multi-question prompts to efficiently collect requirements across core goals, technical layers, quality attributes, integrations, and dependencies
Generates 2-3 design approach options
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionfeature-design-assistantExecute the skills CLI command in your project's root directory to begin installation:
Fetches feature-design-assistant from davila7/claude-code-templates and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate feature-design-assistant. Access via /feature-design-assistant in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Help turn ideas into fully formed designs and specs through structured information gathering and collaborative validation.
Announce at start: "I'm using the feature-design-assistant skill to design this feature."
First, explore the codebase to understand:
Use AskUserQuestion to batch collect information efficiently. Each call can ask up to 4 questions.
{
"questions": [
{
"question": "What is the primary goal of this feature?",
"header": "Goal",
"multiSelect": false,
"options": [
{ "label": "New Functionality", "description": "Add entirely new capability to the system" },
{ "label": "Enhancement", "description": "Improve or extend existing feature" },
{ "label": "Bug Fix", "description": "Fix incorrect behavior or issue" },
{ "label": "Refactoring", "description": "Improve code quality without changing behavior" }
]
},
{
"question": "Who are the primary users of this feature?",
"header": "Users",
"multiSelect": true,
"options": [
{ "label": "End Users", "description": "External customers using the product" },
{ "label": "Admins", "description": "Internal administrators or operators" },
{ "label": "Developers", "description": "Other developers using APIs or SDKs" },
{ "label": "System", "description": "Automated processes or background jobs" }
]
},
{
"question": "What is the expected scope of this feature?",
"header": "Scope",
"multiSelect": false,
"options": [
{ "label": "Small (1-2 days)", "description": "Single component, limited changes" },
{ "label": "Medium (3-5 days)", "description": "Multiple components, moderate complexity" },
{ "label": "Large (1-2 weeks)", "description": "Cross-cutting concerns, significant changes" },
{ "label": "Unsure", "description": "Need to explore further to estimate" }
]
},
{
"question": "Are there any hard deadlines or constraints?",
"header": "Timeline",
"multiSelect": false,
"options": [
{ "label": "Urgent", "description": "Need this ASAP, within days" },
{ "label": "This Sprint", "description": "Should be done within current sprint" },
{ "label": "Flexible", "description": "No hard deadline, quality over speed" },
{ "label": "Planning Only", "description": "Just designing now, implementing later" }
]
}
]
}
{
"questions": [
{
"question": "Which layers of the system will this feature touch?",
"header": "Layers",
"multiSelect": true,
"options": [
{ "label": "Data Model", "description": "Database schema, models, migrations" },
{ "label": "Business Logic", "description": "Services, domain logic, rules" },
{ "label": "API", "description": "REST/GraphQL endpoints, contracts" },
{ "label": "UI", "description": "Frontend components, user interface" }
]
},
{
"question": "What are the key quality requirements?",
"header": "Quality",
"multiSelect": true,
"options": [
{ "label": "High Performance", "description": "Must handle high load or be very fast" },
{ "label": "Strong Security", "description": "Sensitive data, auth, access control" },
{ "label": "High Reliability", "description": "Cannot fail, needs redundancy" },
{ "label": "Easy Maintenance", "description": "Needs to be easily understood and modified" }
]
},
{
"question": "How should errors be handled?",
"header": "Errors",
"multiSelect": false,
"options": [
{ "label": "Fail Fast", "description": "Stop immediately on any error" },
{ "label": "Graceful Degrade", "description": "Continue with reduced functionality" },
{ "label": "Retry & Recover", "description": "Automatic retry with recovery logic" },
{ "label": "Context Dependent", "description": "Different strategies for different cases" }
]
},
{
"question": "What testing approach is preferred?",
"header": "Testing",
"multiSelect": false,
"options": [
{ "label": "TDD (Recommended)", "description": "Write tests first, then implementation" },
{ Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
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4.7★★★★★72 reviews- AAmina Anderson★★★★★Dec 24, 2024
Useful defaults in feature-design-assistant — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- AAmina Lopez★★★★★Dec 24, 2024
feature-design-assistant is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- AAmina Garcia★★★★★Dec 16, 2024
Solid pick for teams standardizing on skills: feature-design-assistant is focused, and the summary matches what you get after install.
- IIsabella Malhotra★★★★★Dec 12, 2024
We added feature-design-assistant from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- SShikha Mishra★★★★★Dec 8, 2024
I recommend feature-design-assistant for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- IIsabella Khanna★★★★★Dec 8, 2024
Registry listing for feature-design-assistant matched our evaluation — installs cleanly and behaves as described in the markdown.
- IIsabella Martin★★★★★Dec 4, 2024
feature-design-assistant has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ZZara Li★★★★★Dec 4, 2024
Useful defaults in feature-design-assistant — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- YYash Thakker★★★★★Nov 27, 2024
feature-design-assistant fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- BBenjamin Khanna★★★★★Nov 23, 2024
Solid pick for teams standardizing on skills: feature-design-assistant is focused, and the summary matches what you get after install.
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