domain-cli▌
zhanghandong/rust-skills · updated Apr 8, 2026
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Rust CLI design constraints and patterns for argument parsing, configuration layering, and user feedback.
- ›Type-safe argument parsing with clap derive macros; supports subcommands, help text, and environment variable integration
- ›Configuration precedence rule: CLI args override environment variables, which override config files and defaults
- ›Proper error handling with stderr/stdout separation, non-zero exit codes, and Result-based error propagation
- ›Progress bars, colored output, and
CLI Domain
Layer 3: Domain Constraints
Domain Constraints → Design Implications
| Domain Rule | Design Constraint | Rust Implication |
|---|---|---|
| User ergonomics | Clear help, errors | clap derive macros |
| Config precedence | CLI > env > file | Layered config loading |
| Exit codes | Non-zero on error | Proper Result handling |
| Stdout/stderr | Data vs errors | eprintln! for errors |
| Interruptible | Handle Ctrl+C | Signal handling |
Critical Constraints
User Communication
RULE: Errors to stderr, data to stdout
WHY: Pipeable output, scriptability
RUST: eprintln! for errors, println! for data
Configuration Priority
RULE: CLI args > env vars > config file > defaults
WHY: User expectation, override capability
RUST: Layered config with clap + figment/config
Exit Codes
RULE: Return non-zero on any error
WHY: Script integration, automation
RUST: main() -> Result<(), Error> or explicit exit()
Trace Down ↓
From constraints to design (Layer 2):
"Need argument parsing"
↓ m05-type-driven: Derive structs for args
↓ clap: #[derive(Parser)]
"Need config layering"
↓ m09-domain: Config as domain object
↓ figment/config: Layer sources
"Need progress display"
↓ m12-lifecycle: Progress bar as RAII
↓ indicatif: ProgressBar
Key Crates
| Purpose | Crate |
|---|---|
| Argument parsing | clap |
| Interactive prompts | dialoguer |
| Progress bars | indicatif |
| Colored output | colored |
| Terminal UI | ratatui |
| Terminal control | crossterm |
| Console utilities | console |
Design Patterns
| Pattern | Purpose | Implementation |
|---|---|---|
| Args struct | Type-safe args | #[derive(Parser)] |
| Subcommands | Command hierarchy | #[derive(Subcommand)] |
| Config layers | Override precedence | CLI > env > file |
| Progress | User feedback | ProgressBar::new(len) |
Code Pattern: CLI Structure
use clap::{Parser, Subcommand};
#[derive(Parser)]
#[command(name = "myapp", about = "My CLI tool")]
struct Cli {
/// Enable verbose output
#[arg(short, long)]
verbose: bool,
#[command(subcommand)]
command: Commands,
}
#[derive(Subcommand)]
enum Commands {
/// Initialize a new project
Init { name: String },
/// Run the application
Run {
#[arg(short, long)]
port: Option<u16>,
},
}
fn main() -> anyhow::Result<()> {
let cli = Cli::parse();
match cli.command {
Commands::Init { name } => init_project(&name)?,
Commands::Run { port } => run_server(port.unwrap_or(8080))?,
}
Ok(())
}
Common Mistakes
| Mistake | Domain Violation | Fix |
|---|---|---|
| Errors to stdout | Breaks piping | eprintln! |
| No help text | Poor UX | #[arg(help = "...")] |
| Panic on error | Bad exit code | Result + proper handling |
| No progress for long ops | User uncertainty | indicatif |
Trace to Layer 1
| Constraint | Layer 2 Pattern | Layer 1 Implementation |
|---|---|---|
| Type-safe args | Derive macros | clap Parser |
| Error handling | Result propagation | anyhow + exit codes |
| User feedback | Progress RAII | indicatif ProgressBar |
| Config precedence | Builder pattern | Layered sources |
Related Skills
| When | See |
|---|---|
| Error handling | m06-error-handling |
| Type-driven args | m05-type-driven |
| Progress lifecycle | m12-lifecycle |
| Async CLI | m07-concurrency |
How to use domain-cli 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 domain-cli
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches domain-cli from GitHub repository zhanghandong/rust-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 domain-cli. Access the skill through slash commands (e.g., /domain-cli) 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
4.8★★★★★59 reviews- ★★★★★Yusuf Yang· Dec 24, 2024
domain-cli reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Advait Iyer· Dec 24, 2024
domain-cli is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Benjamin Kapoor· Dec 20, 2024
Registry listing for domain-cli matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Dhruvi Jain· Dec 16, 2024
I recommend domain-cli for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Yusuf White· Dec 16, 2024
domain-cli has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Anika Khan· Dec 16, 2024
domain-cli reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Benjamin Gupta· Nov 15, 2024
domain-cli has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Yusuf Jackson· Nov 15, 2024
Keeps context tight: domain-cli is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Oshnikdeep· Nov 7, 2024
Solid pick for teams standardizing on skills: domain-cli is focused, and the summary matches what you get after install.
- ★★★★★Advait Gupta· Nov 7, 2024
domain-cli reduced setup friction for our internal harness; good balance of opinion and flexibility.
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