pnpm

antfu/skills · updated Jun 2, 2026

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$npx skills add https://github.com/antfu/skills --skill pnpm
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summary

Fast, disk-efficient Node.js package manager with strict dependency resolution and monorepo support.

  • Enforces strict dependency resolution by default, preventing phantom dependencies; uses content-addressable storage to deduplicate packages across projects
  • Supports monorepo workspaces with filtering, shared lockfiles, and workspace protocol; configuration via pnpm-workspace.yaml
  • Includes advanced dependency management: catalogs for centralized version control, overrides to force spec
skill.md

pnpm is a fast, disk space efficient package manager. It uses a content-addressable store to deduplicate packages across all projects on a machine, saving significant disk space. pnpm enforces strict dependency resolution by default, preventing phantom dependencies. Configuration should preferably be placed in pnpm-workspace.yaml for pnpm-specific settings.

Important: When working with pnpm projects, agents should check for pnpm-workspace.yaml and .npmrc files to understand workspace structure and configuration. Always use --frozen-lockfile in CI environments.

The skill is based on pnpm 10.x, generated at 2026-01-28.

Core

Topic Description Reference
CLI Commands Install, add, remove, update, run, exec, dlx, and workspace commands core-cli
Configuration pnpm-workspace.yaml, .npmrc settings, and package.json fields core-config
Workspaces Monorepo support with filtering, workspace protocol, and shared lockfile core-workspaces
Store Content-addressable storage, hard links, and disk efficiency core-store

Features

Topic Description Reference
Catalogs Centralized dependency version management for workspaces features-catalogs
Overrides Force specific versions of dependencies including transitive features-overrides
Patches Modify third-party packages with custom fixes features-patches
Aliases Install packages under custom names using npm: protocol features-aliases
Hooks Customize resolution with .pnpmfile.cjs hooks features-hooks
Peer Dependencies Auto-install, strict mode, and dependency rules features-peer-deps

Best Practices

Topic Description Reference
CI/CD Setup GitHub Actions, GitLab CI, Docker, and caching strategies best-practices-ci
Migration Migrating from npm/Yarn, handling phantom deps, monorepo migration best-practices-migration
Performance Install optimizations, store caching, workspace parallelization best-practices-performance
how to use pnpm

How to use pnpm 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 pnpm
2

Execute installation command

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

$npx skills add https://github.com/antfu/skills --skill pnpm

The skills CLI fetches pnpm from GitHub repository antfu/skills 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/pnpm

Reload or restart Cursor to activate pnpm. Access the skill through slash commands (e.g., /pnpm) 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

4.540 reviews
  • Carlos Rao· Dec 24, 2024

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

  • Charlotte Ramirez· Dec 20, 2024

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

  • Pratham Ware· Dec 16, 2024

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

  • Noah Harris· Dec 16, 2024

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

  • Chaitanya Patil· Dec 12, 2024

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

  • Amelia Iyer· Nov 19, 2024

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

  • Amelia Gupta· Nov 15, 2024

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

  • Carlos Patel· Nov 11, 2024

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

  • Naina Smith· Nov 7, 2024

    pnpm reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Piyush G· Nov 3, 2024

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

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