golang-samber-mo

samber/cc-skills-golang · updated Apr 8, 2026

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$npx skills add https://github.com/samber/cc-skills-golang --skill golang-samber-mo
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summary

Persona: You are a Go engineer bringing functional programming safety to Go. You use monads to make impossible states unrepresentable — nil checks become type constraints, error handling becomes composable pipelines.

skill.md

Persona: You are a Go engineer bringing functional programming safety to Go. You use monads to make impossible states unrepresentable — nil checks become type constraints, error handling becomes composable pipelines.

Thinking mode: Use ultrathink when designing multi-step Option/Result/Either pipelines. Wrong type choice creates unnecessary wrapping/unwrapping that defeats the purpose of monads.

samber/mo — Monads and Functional Abstractions for Go

Go 1.18+ library providing type-safe monadic types with zero dependencies. Inspired by Scala, Rust, and fp-ts.

Official Resources:

This skill is not exhaustive. Please refer to library documentation and code examples for more information. Context7 can help as a discoverability platform.

go get github.com/samber/mo

For an introduction to functional programming concepts and why monads are valuable in Go, see Monads Guide.

Core Types at a Glance

Type Purpose Think of it as...
Option[T] Value that may be absent Rust's Option, Java's Optional
Result[T] Operation that may fail Rust's Result<T, E>, replaces (T, error)
Either[L, R] Value of one of two types Scala's Either, TypeScript discriminated union
EitherX[L, R] Value of one of X types Scala's Either, TypeScript discriminated union
Future[T] Async value not yet available JavaScript Promise
IO[T] Lazy synchronous side effect Haskell's IO
Task[T] Lazy async computation fp-ts Task
State[S, A] Stateful computation Haskell's State monad

Option[T] — Nullable Values Without nil

Represents a value that is either present (Some) or absent (None). Eliminates nil pointer risks at the type level.

import "github.com/samber/mo"

name := mo.Some("Alice")          // Option[string] with value
empty := mo.None[string]()        // Option[string] without value
fromPtr := mo.PointerToOption(ptr) // nil pointer -> None

// Safe extraction
name.OrElse("Anonymous")  // "Alice"
empty.OrElse("Anonymous")  // "Anonymous"

// Transform if present, skip if absent
upper := name.Map(func(s string) (string, bool) {
    return strings.ToUpper(s), true
})

Key methods: Some, None, Get, MustGet, OrElse, OrEmpty, Map, FlatMap, Match, ForEach, ToPointer, IsPresent, IsAbsent.

Option implements json.Marshaler/Unmarshaler, sql.Scanner, driver.Valuer — use it directly in JSON structs and database models.

For full API reference, see Option Reference.

Result[T] — Error Handling as Values

Represents success (Ok) or failure (Err). Equivalent to Either[error, T] but specialized for Go's error pattern.

// Wrap Go's (value, error) pattern
result := mo.TupleToResult(os.ReadFile("config.yaml"))

// Same-type transform — errors short-circuit automatically
upper := mo.Ok("hello").Map(func(s string) (string, error) {
    return strings.ToUpper(s), nil
})
// Ok("HELLO")

// Extract with fallback
val := upper.OrElse("default")

Go limitation: Direct methods (.Map, .FlatMap) cannot change the type parameter — Result[T].Map returns Result[T], not Result[U]. Go methods cannot introduce new type parameters. For type-changing transforms (e.g. Result[[]byte] to Result[Config]), use sub-package functions or mo.Do:

import "github.com/samber/mo/result"

// Type-changing pipeline: []byte -> Config -> ValidConfig
parsed := result.Pipe2(
    mo.TupleToResult(os.ReadFile("config.yaml")),
    result.Map(func(data []byte) Config { return parseConfig(data) }),
    result.FlatMap(func(cfg Config) mo.Result[ValidConfig] { return validate(cfg) }),
)

Key methods: Ok, Err, Errf, TupleToResult, Try, Get, MustGet, OrElse, Map, FlatMap, MapErr, Match, ForEach, ToEither, IsOk, IsError.

For full API reference, see Result Reference.

Either[L, R] — Discriminated Union of Two Types

Represents a value that is one of two possible types. Unlike Result, neither side implies success or failure — both are valid alternatives.

// API that returns either cached data or fresh data
func fetchUser(id string) mo.Either[CachedUser, FreshUser] {
    if cached, ok := cache.Get(id); ok {
        return mo.Left[CachedUser, FreshUser](cached)
    }
    return mo.Right[CachedUser, FreshUser](db.Fetch(id))
}

// Pattern match
result.Match(
    func(cached CachedUser) mo.Either[CachedUser, FreshUser] { /* use cached */ },
    func(fresh FreshUser) mo.Either[CachedUser, FreshUser] { /* use fresh */ },
)

When to use Either vs Result: Use Result[T] when one path is an error. Use Either[L, R] when both paths are valid alternatives (cached vs fresh, left vs right, strategy A vs B).

Either3[T1, T2, T3], Either4, and Either5 extend this to 3-5 type variants.

For full API reference, see Either Reference.

Do Notation — Imperative Style with Monadic Safety

mo.Do wraps imperative code in a Result, catching panics from MustGet() calls:

result := mo.Do(func() int {
    // MustGet panics on None/Err — Do catches it as Result error
    a := mo.Some(21).MustGet()
    b := mo.Ok(2).MustGet()
    return a * b  // 42
})
// result is Ok(42)

result := mo.Do(func() int {
    val := mo.None[int]().MustGet()  // panics
    return val
})
// result is Err("no such element")

Do notation bridges imperative Go style with monadic safety — write straight-line code, get automatic error propagation.

Pipeline Sub-Packages vs Direct Chaining

samber/mo provides two ways to compose operations:

Direct methods (.Map, .FlatMap) — work when the output type equals the input type:

opt := mo.Some(42)
doubled := opt.Map(func(v int) (int, bool) {
    return v * 2, true
})  // Option[int]

Sub-package functions (option.Map, result.Map) — required when the output type differs from input:

import "github.com/samber/mo/option"

// int -> string type change: use sub-package Map
strOpt := option.Map(func(v int) string {
    return fmt.Sprintf("value: %d", v)
})(mo.Some(
how to use golang-samber-mo

How to use golang-samber-mo 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 golang-samber-mo
2

Execute installation command

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

$npx skills add https://github.com/samber/cc-skills-golang --skill golang-samber-mo

The skills CLI fetches golang-samber-mo from GitHub repository samber/cc-skills-golang 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/golang-samber-mo

Reload or restart Cursor to activate golang-samber-mo. Access the skill through slash commands (e.g., /golang-samber-mo) 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

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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. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 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

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.639 reviews
  • Chen Sanchez· Dec 28, 2024

    Registry listing for golang-samber-mo matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Chaitanya Patil· Dec 24, 2024

    We added golang-samber-mo from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • James Shah· Dec 16, 2024

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

  • Arya Mensah· Dec 4, 2024

    Keeps context tight: golang-samber-mo is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Alexander Garcia· Dec 4, 2024

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

  • Alexander Liu· Nov 23, 2024

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

  • Ren Wang· Nov 19, 2024

    golang-samber-mo reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Piyush G· Nov 15, 2024

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

  • Alexander Farah· Oct 14, 2024

    golang-samber-mo fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Dev Robinson· Oct 10, 2024

    We added golang-samber-mo from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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