nx-generate

nrwl/nx-ai-agents-config · updated Apr 8, 2026

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$npx skills add https://github.com/nrwl/nx-ai-agents-config --skill nx-generate
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summary

Scaffold projects, libraries, and code using Nx generators with workspace pattern consistency.

  • Discovers and runs Nx generators for creating apps, libraries, features, and custom workspace artifacts
  • Prioritizes local workspace generators over plugin generators to maintain repo-specific conventions
  • Performs dry-run validation before execution to verify correct file placement and structure
  • Reads generator source code to understand actual behavior beyond schema, ensuring generated co
skill.md

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

Key Principles

  1. Always use --no-interactive - Prevents prompts that would hang execution
  2. Read the generator source code - The schema alone is not enough; understand what the generator actually does
  3. Match existing repo patterns - Study similar artifacts in the repo and follow their conventions
  4. Verify with lint/test/build/typecheck etc. - Generated code must pass verification. The listed targets are just an example, use what's appropriate for this workspace.

Steps

1. Discover 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) and local workspace generators.

2. Match Generator to User Request

Identify which generator(s) could fulfill the user's needs. Consider what artifact type they want, which framework is relevant, and any specific generator names mentioned.

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.

If no suitable generator exists, you can stop using this skill. However, the burden of proof is high—carefully consider all available generators before deciding none apply.

3. Get Generator Options

Use the --help flag to understand available options:

npx nx g @nx/react:library --help

Pay attention to required options, defaults that might need overriding, and options relevant to the user's request.

Library Buildability

Default to non-buildable libraries unless there's a specific reason for buildable.

Type When to use Generator flags
Non-buildable (default) Internal monorepo libs consumed by apps No --bundler flag
Buildable Publishing to npm, cross-repo sharing, stable libs for cache hits --bundler=vite or --bundler=swc

Non-buildable libs:

  • Export .ts/.tsx source directly
  • Consumer's bundler compiles them
  • Faster dev experience, less config

Buildable libs:

  • Have their own build target
  • Useful for stable libs that rarely change (cache hits)
  • Required for npm publishing

If unclear, ask the user: "Should this library be buildable (own build step, better caching) or non-buildable (source consumed directly, simpler setup)?"

4. Read Generator Source Code

This step is critical. The schema alone does not tell you everything. Reading the source code helps you:

  • Know exactly what files will be created/modified and where
  • Understand side effects (updating configs, installing deps, etc.)
  • Identify behaviors and options not obvious from the schema
  • Understand how options interact with each other

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: Typically in tools/generators/ or a local plugin directory. Search the repo for the generator name.

After reading the source, reconsider: Is this the right generator? If not, go back to step 2.

⚠️ --directory flag behavior can be misleading. It should specify the full path of the generated library or component, not the parent path that it will be generated in.

# ✅ Correct - directory is the full path for the library
nx g @nx/react:library --directory=libs/my-lib
# generates libs/my-lib/package.json and more

# ❌ Wrong - this will create files at libs and libs/src/...
nx g @nx/react:library --name=my-lib --directory=libs
# generates libs/package.json and more

5. Examine Existing Patterns

Before generating, examine the target area of the codebase:

  • Look at similar existing artifacts (other libraries, applications, etc.)
  • Identify naming conventions, file structures, and configuration patterns
  • Note which test runners, build tools, and linters are used
  • Configure the generator to match these patterns

6. Dry-Run to Verify File Placement

Always run with --dry-run first to verify files will be created in the correct location:

npx nx g @nx/react:library --name=my-lib --dry-run --no-interactive

Review the output carefully. If files would be created in the wrong location, adjust your options based on what you learned from the generator source code.

Note: Some generators don't support dry-run (e.g., if they install npm packages). If dry-run fails for this reason, proceed to running the generator for real.

7. Run the Generator

Execute the generator:

nx generate <generator-name> <options> --no-interactive

Tip: New packages often need workspace dependencies wired up (e.g., importing shared types, being consumed by apps). The link-workspace-packages skill can help add these correctly.

8. Modify Generated Code (If Needed)

Generators provide a starting point. Modify the output as needed to:

  • Add or modify functionality as requested
  • Adjust imports, exports, or configurations
  • Integrate with existing code patterns

Important: If you replace or delete generated test files (e.g., *.spec.ts), either write meaningful replacement tests or remove the test target from the project configuration. Empty test suites will cause nx test to fail.

9. Format and Verify

Format all generated/modified files:

nx format --fix

This example is for built-in nx formatting with prettier. There might be other formatting tools for this workspace, use these when appropriate.

Then verify the generated code works. Keep in mind that the changes you make with a generator or subsequent modifications might impact various projects so it's usually not enough to only run targets for the artifact you just created.

# these targets are just an example!
nx run-many -t build,lint,test,typecheck

These targets are common examples used across many workspaces. You should do research into other targets available for this workspace and its projects. CI configuration is usually a good guide for what the critical targets are that have to pass.

If verification fails with manageable issues (a few lint errors, minor type issues), fix them. If issues are extensive, attempt obvious fixes first, then escalate to the user with details about what was generated, what's failing, and what you've attempted.

how to use nx-generate

How to use nx-generate on Cursor

AI-first code editor with Composer

1

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
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/nrwl/nx-ai-agents-config --skill nx-generate

The skills CLI fetches nx-generate from GitHub repository nrwl/nx-ai-agents-config and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/nx-generate

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

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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. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 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

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.853 reviews
  • Nikhil Chen· Dec 28, 2024

    Solid pick for teams standardizing on skills: nx-generate is focused, and the summary matches what you get after install.

  • Nikhil Abebe· Dec 28, 2024

    nx-generate fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Daniel Diallo· Dec 24, 2024

    I recommend nx-generate for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Aarav Menon· Dec 20, 2024

    nx-generate reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Harper Lopez· Dec 12, 2024

    Registry listing for nx-generate matched our evaluation — installs cleanly and behaves as described in the markdown.

  • James Thompson· Nov 19, 2024

    nx-generate has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ama Khanna· Nov 19, 2024

    Registry listing for nx-generate matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Amelia Kapoor· Nov 3, 2024

    nx-generate fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Arya Ramirez· Oct 22, 2024

    nx-generate is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Xiao Sethi· Oct 10, 2024

    Useful defaults in nx-generate — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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