shell

pproenca/dot-skills · updated May 28, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/pproenca/dot-skills --skill shell
0 commentsdiscussion
summary

Comprehensive best practices guide for shell scripting, designed for AI agents and LLMs. Contains 49 rules across 9 categories, prioritized by impact from critical (safety, portability) to incremental (style). Each rule includes detailed explanations, real-world examples comparing incorrect vs. correct implementations, and specific impact metrics.

skill.md

Shell Scripts Best Practices (Community)

Comprehensive best practices guide for shell scripting, designed for AI agents and LLMs. Contains 49 rules across 9 categories, prioritized by impact from critical (safety, portability) to incremental (style). Each rule includes detailed explanations, real-world examples comparing incorrect vs. correct implementations, and specific impact metrics.

When to Apply

Reference these guidelines when:

  • Writing new bash or POSIX shell scripts
  • Reviewing shell scripts for security vulnerabilities
  • Debugging scripts that fail silently or behave unexpectedly
  • Porting scripts between Linux, macOS, and containers
  • Optimizing shell script performance
  • Setting up CI/CD pipelines with shell scripts

Rule Categories by Priority

Priority Category Impact Prefix Rules
1 Safety & Security CRITICAL safety- 6
2 Portability CRITICAL port- 5
3 Error Handling HIGH err- 8
4 Variables & Data HIGH var- 5
5 Quoting & Expansion MEDIUM-HIGH quote- 6
6 Functions & Structure MEDIUM func- 5
7 Testing & Conditionals MEDIUM test- 5
8 Performance LOW-MEDIUM perf- 6
9 Style & Formatting LOW style- 3

Quick Reference

1. Safety & Security (CRITICAL)

2. Portability (CRITICAL)

3. Error Handling (HIGH)

4. Variables & Data (HIGH)

5. Quoting & Expansion (MEDIUM-HIGH)

6. Functions & Structure (MEDIUM)

7. Testing & Conditionals (MEDIUM)

8. Performance (LOW-MEDIUM)

9. Style & Formatting (LOW)

How to Use

Read individual reference files for detailed explanations and code examples:

Reference Files

File Description
AGENTS.md Complete compiled guide with all rules
references/_sections.md Category definitions and ordering
assets/templates/_template.md Template for new rules
metadata.json Version and reference information

Key Sources

how to use shell

How to use shell 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 shell
2

Execute installation command

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

$npx skills add https://github.com/pproenca/dot-skills --skill shell

The skills CLI fetches shell from GitHub repository pproenca/dot-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/shell

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

GET_STARTED →

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)
  • No comments yet — start the thread.
general reviews

Ratings

4.672 reviews
  • Anaya Ghosh· Dec 28, 2024

    We added shell from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Hana Tandon· Dec 20, 2024

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

  • Mateo Martinez· Dec 16, 2024

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

  • Hassan Desai· Dec 16, 2024

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

  • Ganesh Mohane· Dec 12, 2024

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

  • Harper Perez· Dec 12, 2024

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

  • Soo Johnson· Dec 12, 2024

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

  • Noor Tandon· Nov 19, 2024

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

  • Hana Nasser· Nov 11, 2024

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

  • Fatima Li· Nov 11, 2024

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

showing 1-10 of 72

1 / 8