nx-run-tasks▌
nrwl/nx-ai-agents-config · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Execute build, test, lint, serve, and other Nx workspace tasks with flexible filtering and caching.
- ›Run single tasks with nx run <project>:<task> or multiple tasks across projects using nx run-many with project filtering by name, pattern, or tag
- ›Use nx affected to run tasks only on changed projects and their dependents, ideal for CI pipelines and large workspaces
- ›Control execution with flags like --parallel , --skipNxCache , --nxBail , and --configuration to customize behav
You can run tasks with Nx in the following way.
Keep in mind that you might have to prefix things with npx/pnpx/yarn if the user doesn't have nx installed globally. Look at the package.json or lockfile to determine which package manager is in use.
For more details on any command, run it with --help (e.g. nx run-many --help, nx affected --help).
Understand which tasks can be run
You can check those via nx show project <projectname> --json, for example nx show project myapp --json. It contains a targets section which has information about targets that can be run. You can also just look at the package.json scripts or project.json targets, but you might miss out on inferred tasks by Nx plugins.
Run a single task
nx run <project>:<task>
where project is the project name defined in package.json or project.json (if present).
Run multiple tasks
nx run-many -t build test lint typecheck
You can pass a -p flag to filter to specific projects, otherwise it runs on all projects. You can also use --exclude to exclude projects, and --parallel to control the number of parallel processes (default is 3).
Examples:
nx run-many -t test -p proj1 proj2— test specific projectsnx run-many -t test --projects=*-app --exclude=excluded-app— test projects matching a patternnx run-many -t test --projects=tag:api-*— test projects by tag
Run tasks for affected projects
Use nx affected to only run tasks on projects that have been changed and projects that depend on changed projects. This is especially useful in CI and for large workspaces.
nx affected -t build test lint
By default it compares against the base branch. You can customize this:
nx affected -t test --base=main --head=HEAD— compare against a specific base and headnx affected -t test --files=libs/mylib/src/index.ts— specify changed files directly
Useful flags
These flags work with run, run-many, and affected:
--skipNxCache— rerun tasks even when results are cached--verbose— print additional information such as stack traces--nxBail— stop execution after the first failed task--configuration=<name>— use a specific configuration (e.g.production)
How to use nx-run-tasks 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-run-tasks
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches nx-run-tasks from GitHub repository nrwl/nx-ai-agents-config 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-run-tasks. Access the skill through slash commands (e.g., /nx-run-tasks) 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
4.8★★★★★50 reviews- ★★★★★Emma Torres· Dec 24, 2024
I recommend nx-run-tasks for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Shikha Mishra· Dec 12, 2024
I recommend nx-run-tasks for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Emma Wang· Dec 12, 2024
Solid pick for teams standardizing on skills: nx-run-tasks is focused, and the summary matches what you get after install.
- ★★★★★Aditi Menon· Dec 8, 2024
nx-run-tasks fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Fatima Abbas· Nov 27, 2024
We added nx-run-tasks from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Diego Nasser· Nov 15, 2024
Solid pick for teams standardizing on skills: nx-run-tasks is focused, and the summary matches what you get after install.
- ★★★★★Rahul Santra· Nov 3, 2024
Solid pick for teams standardizing on skills: nx-run-tasks is focused, and the summary matches what you get after install.
- ★★★★★Aditi Mehta· Nov 3, 2024
I recommend nx-run-tasks for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Pratham Ware· Oct 22, 2024
nx-run-tasks is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Fatima Wang· Oct 22, 2024
Keeps context tight: nx-run-tasks is the kind of skill you can hand to a new teammate without a long onboarding doc.
showing 1-10 of 50