cpp-coding-standards

affaan-m/everything-claude-code · updated Apr 8, 2026

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$npx skills add https://github.com/affaan-m/everything-claude-code --skill cpp-coding-standards
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summary

Modern C++ standards enforcing type safety, resource management, and clarity through the C++ Core Guidelines.

  • Covers six foundational principles: RAII for resource lifetime, immutability by default, compile-time type safety, intent-driven naming, minimal complexity, and value semantics over pointers
  • Provides detailed rules across 15+ domains including functions, classes, resource management, error handling, concurrency, templates, and standard library usage with code examples for each \
skill.md

C++ Coding Standards (C++ Core Guidelines)

Comprehensive coding standards for modern C++ (C++17/20/23) derived from the C++ Core Guidelines. Enforces type safety, resource safety, immutability, and clarity.

When to Use

  • Writing new C++ code (classes, functions, templates)
  • Reviewing or refactoring existing C++ code
  • Making architectural decisions in C++ projects
  • Enforcing consistent style across a C++ codebase
  • Choosing between language features (e.g., enum vs enum class, raw pointer vs smart pointer)

When NOT to Use

  • Non-C++ projects
  • Legacy C codebases that cannot adopt modern C++ features
  • Embedded/bare-metal contexts where specific guidelines conflict with hardware constraints (adapt selectively)

Cross-Cutting Principles

These themes recur across the entire guidelines and form the foundation:

  1. RAII everywhere (P.8, R.1, E.6, CP.20): Bind resource lifetime to object lifetime
  2. Immutability by default (P.10, Con.1-5, ES.25): Start with const/constexpr; mutability is the exception
  3. Type safety (P.4, I.4, ES.46-49, Enum.3): Use the type system to prevent errors at compile time
  4. Express intent (P.3, F.1, NL.1-2, T.10): Names, types, and concepts should communicate purpose
  5. Minimize complexity (F.2-3, ES.5, Per.4-5): Simple code is correct code
  6. Value semantics over pointer semantics (C.10, R.3-5, F.20, CP.31): Prefer returning by value and scoped objects

Philosophy & Interfaces (P., I.)

Key Rules

Rule Summary
P.1 Express ideas directly in code
P.3 Express intent
P.4 Ideally, a program should be statically type safe
P.5 Prefer compile-time checking to run-time checking
P.8 Don't leak any resources
P.10 Prefer immutable data to mutable data
I.1 Make interfaces explicit
I.2 Avoid non-const global variables
I.4 Make interfaces precisely and strongly typed
I.11 Never transfer ownership by a raw pointer or reference
I.23 Keep the number of function arguments low

DO

// P.10 + I.4: Immutable, strongly typed interface
struct Temperature {
    double kelvin;
};

Temperature boil(const Temperature& water);

DON'T

// Weak interface: unclear ownership, unclear units
double boil(double* temp);

// Non-const global variable
int g_counter = 0;  // I.2 violation

Functions (F.*)

Key Rules

Rule Summary
F.1 Package meaningful operations as carefully named functions
F.2 A function should perform a single logical operation
F.3 Keep functions short and simple
F.4 If a function might be evaluated at compile time, declare it constexpr
F.6 If your function must not throw, declare it noexcept
F.8 Prefer pure functions
F.16 For "in" parameters, pass cheaply-copied types by value and others by const&
F.20 For "out" values, prefer return values to output parameters
F.21 To return multiple "out" values, prefer returning a struct
F.43 Never return a pointer or reference to a local object

Parameter Passing

// F.16: Cheap types by value, others by const&
void print(int x);                           // cheap: by value
void analyze(const std::string& data);       // expensive: by const&
void transform(std::string s);               // sink: by value (will move)

// F.20 + F.21: Return values, not output parameters
struct ParseResult {
    std::string token;
    int position;
};

ParseResult parse(std::string_view input);   // GOOD: return struct

// BAD: output parameters
void parse(std::string_view input,
           std::string& token, int& pos);    // avoid this

Pure Functions and constexpr

// F.4 + F.8: Pure, constexpr where possible
constexpr int factorial(int n) noexcept {
    return (n <= 1) ? 1 : n * factorial(n - 1);
}

static_assert(factorial(5) == 120);

Anti-Patterns

  • Returning T&& from functions (F.45)
  • Using va_arg / C-style variadics (F.55)
  • Capturing by reference in lambdas passed to other threads (F.53)
  • Returning const T which inhibits move semantics (F.49)

Classes & Class Hierarchies (C.*)

Key Rules

Rule Summary
C.2 Use class if invariant exists; struct if data members vary independently
C.9 Minimize exposure of members
C.20 If you can avoid defining default operations, do (Rule of Zero)
C.21 If you define or =delete any copy/move/destructor, handle them all (Rule of Five)
C.35 Base class destructor: public virtual or protected non-virtual
C.41 A constructor should create a fully initialized object
C.46 Declare single-argument constructors explicit
C.67 A polymorphic class should suppress public copy/move
C.128 Virtual functions: specify exactly one of virtual, override, or final

Rule of Zero

// C.20: Let the compiler generate special members
struct Employee {
    std::string name;
    std::string department;
    int id;
    // No destructor, copy/move constructors, or assignment operators needed
};

Rule of Five

// C.21: If you must manage a resource, define all five
class Buffer {
public:
    explicit Buffer(std::size_t size)
        : data_(std::make_unique<char[]>(size)), size_(size) {}

    ~Buffer() = default;

    Buffer(const Buffer& other)
        : data_(std::make_unique<char[]>(other.size_)), size_(other.size_) {
        std::copy_n(other.data_.get(), size_, data_.get());
    }

    Buffer& operator=(const Buffer& other) {
        if (this != &other) {
            auto new_data = std::make_unique<char[]>(other.size_);
            std::copy_n(other.data_.get(), other.size_, new_data.get());
            data_ = std::move(new_data);
            size_ = other.size_;
        }
        return *this;
    }

    Buffer(Buffer&&) noexcept = default;
    Buffer& operator=(Buffer&&) noexcept = default;

private:
    std::unique_ptr<char[]> data_;
    std::size_t size_;
};

Class Hierarchy

// C.35 + C.128: Virtual destructor, use override
class Shape {
public:
    virtual ~Shape() = default;
    virtual double area() const 
how to use cpp-coding-standards

How to use cpp-coding-standards 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 cpp-coding-standards
2

Execute installation command

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

$npx skills add https://github.com/affaan-m/everything-claude-code --skill cpp-coding-standards

The skills CLI fetches cpp-coding-standards from GitHub repository affaan-m/everything-claude-code 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/cpp-coding-standards

Reload or restart Cursor to activate cpp-coding-standards. Access the skill through slash commands (e.g., /cpp-coding-standards) 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.

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

Ratings

4.739 reviews
  • Tariq Desai· Dec 8, 2024

    cpp-coding-standards reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Amelia Park· Dec 4, 2024

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

  • Tariq Park· Nov 27, 2024

    Registry listing for cpp-coding-standards matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Kofi Lopez· Nov 23, 2024

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

  • Kofi Ndlovu· Oct 18, 2024

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

  • Tariq Chawla· Oct 14, 2024

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

  • Aditi Smith· Sep 25, 2024

    Keeps context tight: cpp-coding-standards is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Amelia Choi· Sep 25, 2024

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

  • Aditi Johnson· Sep 21, 2024

    Registry listing for cpp-coding-standards matched our evaluation — installs cleanly and behaves as described in the markdown.

  • William Tandon· Sep 17, 2024

    We added cpp-coding-standards from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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