m05-type-driven

zhanghandong/rust-skills · updated Apr 8, 2026

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$npx skills add https://github.com/zhanghandong/rust-skills --skill m05-type-driven
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summary

Compile-time state validation through type encoding, eliminating invalid states at the type level.

  • Covers six core patterns: newtype for type-safe primitives, type state for state machines, PhantomData for variance tracking, marker traits for capability flags, builders for gradual construction, and sealed traits for closed impl sets
  • Emphasizes asking \"can the compiler catch this?\" before adding runtime validation, with decision guides mapping common needs to appropriate patterns
  • In
skill.md

Type-Driven Design

Layer 1: Language Mechanics

Core Question

How can the type system prevent invalid states?

Before reaching for runtime checks:

  • Can the compiler catch this error?
  • Can invalid states be unrepresentable?
  • Can the type encode the invariant?

Error → Design Question

Pattern Don't Just Say Ask Instead
Primitive obsession "It's just a string" What does this value represent?
Boolean flags "Add an is_valid flag" Can states be types?
Optional everywhere "Check for None" Is absence really possible?
Validation at runtime "Return Err if invalid" Can we validate at construction?

Thinking Prompt

Before adding runtime validation:

  1. Can the type encode the constraint?

    • Numeric range → bounded types or newtypes
    • Valid states → type state pattern
    • Semantic meaning → newtype
  2. When is validation possible?

    • At construction → validated newtype
    • At state transition → type state
    • Only at runtime → Result with clear error
  3. Who needs to know the invariant?

    • Compiler → type-level encoding
    • API users → clear type signatures
    • Runtime only → documentation

Trace Up ↑

When type design is unclear:

"Need to validate email format"
    ↑ Ask: Is this a domain value object?
    ↑ Check: m09-domain (Email as Value Object)
    ↑ Check: domain-* (validation requirements)
Situation Trace To Question
What types to create m09-domain What's the domain model?
State machine design m09-domain What are valid transitions?
Marker trait usage m04-zero-cost Static or dynamic dispatch?

Trace Down ↓

From design to implementation:

"Need type-safe wrapper for primitives"
    ↓ Newtype: struct UserId(u64);

"Need compile-time state validation"
    ↓ Type State: Connection<Connected>

"Need to track phantom type parameters"
    ↓ PhantomData: PhantomData<T>

"Need capability markers"
    ↓ Marker Trait: trait Validated {}

"Need gradual construction"
    ↓ Builder: Builder::new().field(x).build()

Quick Reference

Pattern Purpose Example
Newtype Type safety struct UserId(u64);
Type State State machine Connection<Connected>
PhantomData Variance/lifetime PhantomData<&'a T>
Marker Trait Capability flag trait Validated {}
Builder Gradual construction Builder::new().name("x").build()
Sealed Trait Prevent external impl mod private { pub trait Sealed {} }

Pattern Examples

Newtype

struct Email(String);  // Not just any string

impl Email {
    pub fn new(s: &str) -> Result<Self, ValidationError> {
        // Validate once, trust forever
        validate_email(s)?;
        Ok(Self(s.to_string()))
    }
}

Type State

struct Connection<State>(TcpStream, PhantomData<State>);

struct Disconnected;
struct Connected;
struct Authenticated;

impl Connection<Disconnected> {
    fn connect(self) -> Connection<Connected> { ... }
}

impl Connection<Connected> {
    fn authenticate(self) -> Connection<Authenticated> { ... }
}

Decision Guide

Need Pattern
Type safety for primitives Newtype
Compile-time state validation Type State
Lifetime/variance markers PhantomData
Capability flags Marker Trait
Gradual construction Builder
Closed set of impls Sealed Trait
Zero-sized type marker ZST struct

Anti-Patterns

Anti-Pattern Why Bad Better
Boolean flags for states Runtime errors Type state
String for semantic types No type safety Newtype
Option for uninitialized Unclear invariant Builder
Public fields with invariants Invariant violation Private + validated new()

Related Skills

When See
Domain modeling m09-domain
Trait design m04-zero-cost
Error handling in constructors m06-error-handling
Anti-patterns m15-anti-pattern
how to use m05-type-driven

How to use m05-type-driven 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 m05-type-driven
2

Execute installation command

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

$npx skills add https://github.com/zhanghandong/rust-skills --skill m05-type-driven

The skills CLI fetches m05-type-driven from GitHub repository zhanghandong/rust-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/m05-type-driven

Reload or restart Cursor to activate m05-type-driven. Access the skill through slash commands (e.g., /m05-type-driven) 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

4.657 reviews
  • Dhruvi Jain· Dec 24, 2024

    m05-type-driven fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Benjamin Chawla· Dec 24, 2024

    Registry listing for m05-type-driven matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Diego Bansal· Dec 12, 2024

    Useful defaults in m05-type-driven — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Diego Kim· Dec 8, 2024

    We added m05-type-driven from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Kabir Patel· Dec 8, 2024

    Solid pick for teams standardizing on skills: m05-type-driven is focused, and the summary matches what you get after install.

  • Benjamin Ghosh· Dec 4, 2024

    I recommend m05-type-driven for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Diego Mensah· Nov 27, 2024

    m05-type-driven reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Benjamin Bhatia· Nov 23, 2024

    Keeps context tight: m05-type-driven is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Oshnikdeep· Nov 15, 2024

    Registry listing for m05-type-driven matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Evelyn Ndlovu· Nov 15, 2024

    m05-type-driven fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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