nx-generate▌
tech-leads-club/agent-skills · updated May 23, 2026
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Generate code using Nx generators — scaffold projects, libraries, features, or run workspace-specific generators with proper discovery, validation, and verification. Use when user says "create a new library", "scaffold a component", "generate code with Nx", "run a generator", "nx generate", or any code scaffolding task in a monorepo. Prefers local workspace-plugin generators over external plugins. Do NOT use for running build/test/lint tasks (use nx-run-tasks) or workspace configuration (use nx-workspace).
| name | nx-generate |
| description | Generate code using Nx generators — scaffold projects, libraries, features, or run workspace-specific generators with proper discovery, validation, and verification. Use when user says "create a new library", "scaffold a component", "generate code with Nx", "run a generator", "nx generate", or any code scaffolding task in a monorepo. Prefers local workspace-plugin generators over external plugins. Do NOT use for running build/test/lint tasks (use nx-run-tasks) or workspace configuration (use nx-workspace). |
Run Nx Generator
Nx generators are powerful tools that scaffold projects, make automated code migrations or automate repetitive tasks in a monorepo. They ensure consistency across the codebase and reduce boilerplate work.
This skill applies when the user wants to:
- Create new projects like libraries or applications
- Scaffold features or boilerplate code
- Run workspace-specific or custom generators
- Do anything else that an nx generator exists for
Generator Discovery Flow
Step 1: List Available Generators
Use the Nx CLI to discover available generators:
- List all generators for a plugin:
npx nx list @nx/react - View available plugins:
npx nx list
This includes:
- Plugin generators (e.g.,
@nx/react:library,@nx/js:library) - Local workspace generators (defined in the repo's own plugins)
Step 2: Match Generator to User Request
Based on the user's request, identify which generator(s) could fulfill their needs. Consider:
- What artifact type they want to create (library, application, etc.)
- Which framework or technology stack is relevant
- Whether they mentioned specific generator names
IMPORTANT: When both a local workspace generator and an external plugin generator could satisfy the request, always prefer the local workspace generator. Local generators are customized for the specific repo's patterns and conventions.
It's possible that the user request is something that no Nx generator exists for whatsoever. In this case, you can stop using this skill and try to help the user another way. HOWEVER, the burden of proof for this is high. Before aborting, carefully consider each and every generator that's available. Look into details for any that could be related in any way before making this decision.
Pre-Execution Checklist
Before running any generator, complete these steps:
1. Fetch Generator Schema
Use the --help flag to understand all available options:
npx nx g @nx/react:library --help
Pay attention to:
- Required options that must be provided
- Optional options that may be relevant to the user's request
- Default values that might need to be overridden
2. Read Generator Source Code
Understanding what the generator actually does helps you:
- Know what files will be created/modified
- Understand any side effects (updating configs, installing deps, etc.)
- Identify options that might not be obvious from the schema
To find generator source code:
- For plugin generators: Use
node -e "console.log(require.resolve('@nx/<plugin>/generators.json'));"to find the generators.json, then locate the source from there - If that fails, read directly from
node_modules/<plugin>/generators.json - For local generators: They are typically in
tools/generators/or a local plugin directory. You can search the repo for the generator name to find it.
2.5 Reevaluate if the generator is right
Once you have built up an understanding of what the selected generator does, reconsider: Is this the right generator to service the user request? If not, it's okay to go back to the Generator Discovery Flow and select a different generator before proceeding. If you do, make sure to go through the entire pre-execution checklist once more.
3. Understand Repo Context
Before generating, examine the target area of the codebase:
- Look at similar existing artifacts (other libraries, applications, etc.)
- Identify patterns and conventions used in the repo
- Note naming conventions, file structures, and configuration patterns
- Try to match these patterns when configuring the generator
For example, if similar libraries are using a specific test runner, build tool or linter, try to match that if possible. If projects or other artifacts are organized with a specific naming convention, try to match it.
4. Validate Required Options
Ensure all required options have values:
- Map the user's request to generator options
- Infer values from context where possible
- Ask the user for any critical missing information
Execution
Keep in mind that you might have to prefix things with npx/pnpx/yarn if the user doesn't have nx installed globally. Many generators will behave differently based on where they are executed. For example, first-party nx library generators use the cwd to determine the directory that the library should be placed in. This is highly important.
Consider Dry-Run (Optional)
Running with --dry-run first is strongly encouraged but not mandatory. Use your judgment:
- For complex generators or unfamiliar territory: do a dry-run first
- For simple, well-understood generators: may proceed directly
- Dry-run shows file names and created/deleted/modified markers, but not content
- There are cases where a generator does not support dry-run (for example if it had to install an npm package) - in that case --dry-run might fail. Don't be discouraged but simply move on to running the generator for real and iterating from there.
Running the Generator
Execute the generator with:
nx generate <generator-name> <options> --no-interactive
CRITICAL: Always include --no-interactive to prevent prompts that would hang the execution.
Example:
nx generate @nx/react:library --name=my-utils --no-interactive
Handling Generator Failures
If the generator fails:
- Diagnose the error - Read the error message carefully
- Identify the cause - Missing options, invalid values, conflicts, etc.
- Attempt automatic fix - Adjust options or resolve conflicts
- Retry - Run the generator again with corrected options
Common failure reasons:
- Missing required options
- Invalid option values
- Conflicting with existing files
- Missing dependencies
- Generator doesn't support certain flag combinations
Post-Generation
1. Modify Generated Code (If Needed)
Generators provide a starting point, but the output may need adjustment to match the user's specific requirements:
- Add or modify functionality as requested
- Adjust imports, exports, or configurations
- Integrate with existing code patterns in the repo
2. Format Code
Run formatting on all generated/modified files:
nx format --fix
Languages other than javascript/typescript might need other formatting invocations too.
3. Run Verification
Verify that the generated code works correctly. What this looks like will vary depending on the type of generator and the targets available. If the generator created a new project, run its targets directly Use your best judgement to determine what needs to be verified.
Example:
nx lint <new-project>
nx test <new-project>
nx build <new-project>
4. Handle Verification Failures
When verification fails:
If scope is manageable (a few lint errors, minor type issues):
- Fix the issues
- Re-run verification to confirm
If issues are extensive (many errors, complex problems):
- Attempt simple, obvious fixes first
- If still failing, escalate to the user with:
- Description of what was generated
- What verification is failing
- What you've attempted to fix
- Remaining issues that need user input
Error Handling
Generator Failures
- Check the error message for specific causes
- Verify all required options are provided
- Check for conflicts with existing files
- Ensure the generator name and options are correct
Missing Options
- Consult the generator schema for required fields
- Infer values from context when reasonable
- Ask the user for values that cannot be inferred
Key Principles
-
Local generators first - Always prefer workspace/local generators over external plugin generators when both could work
-
Understand before running - Read both the schema AND the source code to fully understand what will happen
-
No prompts - Always use
--no-interactiveto prevent hanging -
Generators are starting points - Modify the output as needed to fully satisfy the user's requirements
-
Verify changes work - Don't just generate; ensure the code builds, lints, and tests pass
-
Be proactive about fixes - Don't just report errors; attempt to resolve them automatically when possible
-
Match repo patterns - Study existing similar code in the repo and match its conventions
How to use nx-generate 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 nx-generate
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches nx-generate from GitHub repository tech-leads-club/agent-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 nx-generate. Access the skill through slash commands (e.g., /nx-generate) 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▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate 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
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★73 reviews- ★★★★★Michael Li· Dec 28, 2024
nx-generate reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Chaitanya Patil· Dec 20, 2024
Useful defaults in nx-generate — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Hana Sanchez· Dec 20, 2024
nx-generate has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Nikhil Choi· Dec 20, 2024
nx-generate is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Henry Desai· Dec 16, 2024
Registry listing for nx-generate matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Aarav Jain· Dec 12, 2024
Useful defaults in nx-generate — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Aarav Patel· Dec 8, 2024
nx-generate fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★James Reddy· Dec 8, 2024
We added nx-generate from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Aarav Sanchez· Nov 27, 2024
nx-generate is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Advait Flores· Nov 27, 2024
Keeps context tight: nx-generate is the kind of skill you can hand to a new teammate without a long onboarding doc.
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