golang-data-structures▌
samber/cc-skills-golang · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Persona: You are a Go engineer who understands data structure internals. You choose the right structure for the job — not the most familiar one — by reasoning about memory layout, allocation cost, and access patterns.
Persona: You are a Go engineer who understands data structure internals. You choose the right structure for the job — not the most familiar one — by reasoning about memory layout, allocation cost, and access patterns.
Go Data Structures
Built-in and standard library data structures: internals, correct usage, and selection guidance. For safety pitfalls (nil maps, append aliasing, defensive copies) see samber/cc-skills-golang@golang-safety skill. For channels and sync primitives see samber/cc-skills-golang@golang-concurrency skill. For string/byte/rune choice see samber/cc-skills-golang@golang-design-patterns skill.
Best Practices Summary
- Preallocate slices and maps with
make(T, 0, n)/make(map[K]V, n)when size is known or estimable — avoids repeated growth copies and rehashing - Arrays SHOULD be preferred over slices only for fixed, compile-time-known sizes (hash digests, IPv4 addresses, matrix dimensions)
- NEVER rely on slice capacity growth timing — the growth algorithm changed between Go versions and may change again; your code should not depend on when a new backing array is allocated
- Use
container/heapfor priority queues,container/listonly when frequent middle insertions are needed,container/ringfor fixed-size circular buffers strings.BuilderMUST be preferred for building strings;bytes.BufferMUST be preferred for bidirectional I/O (implements bothio.Readerandio.Writer)- Generic data structures SHOULD use the tightest constraint possible —
comparablefor keys, custom interfaces for ordering unsafe.PointerMUST only follow the 6 valid conversion patterns from the Go spec — NEVER store in auintptrvariable across statementsweak.Pointer[T](Go 1.24+) SHOULD be used for caches and canonicalization maps to allow GC to reclaim entries
Slice Internals
A slice is a 3-word header: pointer, length, capacity. Multiple slices can share a backing array (→ see samber/cc-skills-golang@golang-safety for aliasing traps and the header diagram).
Capacity Growth
- < 256 elements: capacity doubles
-
= 256 elements: grows by ~25% (
newcap += (newcap + 3*256) / 4) - Each growth copies the entire backing array — O(n)
Preallocation
// Exact size known
users := make([]User, 0, len(ids))
// Approximate size known
results := make([]Result, 0, estimatedCount)
// Pre-grow before bulk append (Go 1.21+)
s = slices.Grow(s, additionalNeeded)
slices Package (Go 1.21+)
Key functions: Sort/SortFunc, BinarySearch, Contains, Compact, Grow. For Clone, Equal, DeleteFunc → see samber/cc-skills-golang@golang-safety skill.
Slice Internals Deep Dive — Full slices package reference, growth mechanics, len vs cap, header copying, backing array aliasing.
Map Internals
Maps are hash tables with 8-entry buckets and overflow chains. They are reference types — assigning a map copies the pointer, not the data.
Preallocation
m := make(map[string]*User, len(users)) // avoids rehashing during population
maps Package Quick Reference (Go 1.21+)
| Function | Purpose |
|---|---|
Collect (1.23+) |
Build map from iterator |
Insert (1.23+) |
Insert entries from iterator |
All (1.23+) |
Iterator over all entries |
Keys, Values |
Iterators over keys/values |
For Clone, Equal, sorted iteration → see samber/cc-skills-golang@golang-safety skill.
Map Internals Deep Dive — How Go maps store and hash data, bucket overflow chains, why maps never shrink (and what to do about it), comparing map performance to alternatives.
Arrays
Fixed-size, value types. Copied entirely on assignment. Use for compile-time-known sizes:
type Digest [32]byte // fixed-size, value type
var grid [3][3]int // multi-dimensional
cache := map[[2]int]Result{} // arrays are comparable — usable as map keys
Prefer slices for everything else — arrays cannot grow and pass by value (expensive for large sizes).
container/ Standard Library
| Package | Data Structure | Best For |
|---|---|---|
container/list |
Doubly-linked list | LRU caches, frequent middle insertion/removal |
container/heap |
Min-heap (priority queue) | Top-K, scheduling, Dijkstra |
container/ring |
Circular buffer | Rolling windows, round-robin |
bufio |
Buffered reader/writer/scanner | Efficient I/O with small reads/writes |
Container types use any (no type safety) — consider generic wrappers. Container Patterns, bufio, and Examples — When to use each container type, generic wrappers to add type safety, and bufio patterns for efficient I/O.
strings.Builder vs bytes.Buffer
Use strings.Builder for pure string concatenation (avoids copy on String()), bytes.Buffer when you need io.Reader or byte manipulation. Both support Grow(n). Details and comparison
Generic Collections (Go 1.18+)
Use the tightest constraint possible. comparable for map keys, cmp.Ordered for sorting, custom interfaces for domain-specific ordering.
type Set[T comparable] map[T]struct{}
func (s Set[T]) Add(v T) { s[v] = struct{}{} }
func (s Set[T]) Contains(v T) bool { _, ok := s[v]; return ok }
Writing Generic Data Structures — Using Go 1.18+ generics for type-safe containers, understanding constraint satisfaction, and building domain-specific generic types.
Pointer Types
| Type | Use Case | Zero Value |
|---|---|---|
*T |
Normal indirection, mutation, optional values | nil |
unsafe.Pointer |
FFI, low-level memory layout (6 spec patterns only) | nil |
weak.Pointer[T] (1.24+) |
Caches, canonicalization, weak references | N/A |
Pointer Types Deep Dive — Normal pointers, unsafe.Pointer (the 6 valid spec patterns), and weak.Pointer[T] for GC-safe caches that don't prevent cleanup.
Copy Semantics Quick Reference
| Type | Copy Behavior | Independence |
|---|---|---|
int, float, bool, string |
Value (deep copy) | Fully independent |
array, struct |
Value (deep copy) | Fully independent |
slice |
Header copied, backing array shared | Use slices.Clone |
map |
Reference copied | Use maps.Clone |
channel |
Reference copied | Same channel |
*T (pointer) |
Address copied | Same underlying value |
interface |
Value copied (type + value pair) | Depends on held type |
Third-Party Libraries
For advanced data structures (trees, sets, queues, stacks) beyond the standard library:
emirpasic/gods— comprehensive collection library (trees, sets, lists, stacks, maps, queues)deckarep/golang-set— thread-safe and non-thread-safe set implementationsgammazero/deque— fast double-ended queue
When using third-party libraries, refer to their official documentation and code examples for current API signatures. Context7 can help as a discoverability platform.
Cross-References
- → See
samber/cc-skills-golang@golang-performanceskill for struct field alignment, memory layout optimization, and cache locality - → See
samber/cc-skills-golang@golang-safetyskill for nil map/slice pitfalls, append aliasing, defensive copying,slices.Clone/Equal - → See
samber/cc-skills-golang@golang-concurrencyskill for channels,sync.Map,sync.Pool, and all sync primitives - → See
samber/cc-skills-golang@golang-design-patternsskill forstringvs[]bytevs[]rune, iterators, streaming - → See
samber/cc-skills-golang@golang-structs-interfacesskill for struct composition, embedding, and generics vsany - → See
samber/cc-skills-golang@golang-code-styleskill for slice/map initialization style
Common Mistakes
| Mistake | Fix |
|---|---|
| Growing a slice in a loop without preallocation | Each growth copies the entire backing array — O(n) per growth. Use make([]T, 0, n) or slices.Grow |
Using container/list when a slice would suffice |
Linked lists have poor cache locality (each node is a separate heap allocation). Benchmark first |
bytes.Buffer for pure string building |
Buffer's String() copies the underlying bytes. strings.Builder avoids this copy |
unsafe.Pointer stored as uintptr across statements |
GC can move the object between statements — the uintptr becomes a dangling reference |
| Large struct values in maps (copying overhead) | Map access copies the entire value. Use map[K]*V for large value types to avoid the copy |
References
How to use golang-data-structures 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 golang-data-structures
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches golang-data-structures from GitHub repository samber/cc-skills-golang 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 golang-data-structures. Access the skill through slash commands (e.g., /golang-data-structures) 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
4.6★★★★★47 reviews- ★★★★★Ren Shah· Dec 28, 2024
I recommend golang-data-structures for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Pratham Ware· Dec 24, 2024
Keeps context tight: golang-data-structures is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Charlotte Abbas· Dec 20, 2024
golang-data-structures reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Aditi Gupta· Dec 4, 2024
Useful defaults in golang-data-structures — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Hiroshi Mehta· Nov 23, 2024
Registry listing for golang-data-structures matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Ren Desai· Nov 19, 2024
golang-data-structures reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Hiroshi Menon· Nov 11, 2024
I recommend golang-data-structures for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ren Jackson· Nov 11, 2024
Keeps context tight: golang-data-structures is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Liam Flores· Oct 14, 2024
golang-data-structures reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ren Khanna· Oct 10, 2024
Registry listing for golang-data-structures matched our evaluation — installs cleanly and behaves as described in the markdown.
showing 1-10 of 47