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FastLED Project Rules for Cursor

Cursor Configuration

Post-Change Hooks

Run linting after every code change:

post_change_hooks:
  - command: "bash lint"
    description: "Run code formatting and linting"
    working_directory: "."

MCP Server Configuration

This project includes a custom MCP server (mcp_server.py) that provides tools for:

Running tests with various options
Compiling examples for different platforms
Code fingerprinting and change detection
Linting and formatting
Project information and status
Build info analysis for platform-specific defines, compiler flags, and toolchain information
Symbol analysis for binary optimization (all platforms)
Stack trace setup for enhanced debugging
🌐 FastLED Web Compiler with Playwright (FOREGROUND AGENTS ONLY)
🚨 CRITICAL: validate_completion tool for background agents

To use the MCP server, run: uv run mcp_server.py

BACKGROUND AGENTS: The MCP server includes a mandatory validate_completion tool that MUST be used before indicating task completion. This tool runs bash test and ensures all tests pass.

FastLED Web Compiler (FOREGROUND AGENTS ONLY)

🌐 FOR INTERACTIVE DEVELOPMENT: The MCP server includes a run_fastled_web_compiler tool that:

Note: For direct command-line WASM compilation, see the WASM Sketch Compilation section below.

Compiles Arduino sketches to WASM for browser execution
Captures console.log output with playwright automation
Takes screenshots of running visualizations
Monitors FastLED_onFrame calls to verify proper initialization
Provides detailed analysis of errors and performance

PREREQUISITES:

pip install fastled - FastLED web compiler
pip install playwright - Browser automation (included in pyproject.toml)
Docker (optional, for faster compilation)

USAGE EXAMPLES:

# Via MCP Server - Basic usage
use run_fastled_web_compiler tool with:
- example_path: "examples/Audio"
- capture_duration: 30
- headless: false
- save_screenshot: true

# Via MCP Server - Different examples
use run_fastled_web_compiler tool with:
- example_path: "examples/Blink"
- capture_duration: 15
- headless: true

# Via MCP Server - Quick test
use run_fastled_web_compiler tool with:
- example_path: "examples/wasm"
- capture_duration: 10

KEY FEATURES:

Automatic browser installation: Installs Chromium via playwright
Console.log capture: Records all browser console output with timestamps
Error detection: Identifies compilation failures and runtime errors
FastLED monitoring: Tracks FastLED_onFrame calls to verify functionality
Screenshot capture: Saves visualization images with timestamps
Docker detection: Checks for Docker availability for faster builds
Background agent protection: Automatically disabled for CI/background environments

🚫 BACKGROUND AGENT RESTRICTION: This tool is COMPLETELY DISABLED for background agents and CI environments. Background agents attempting to use this tool will receive an error message. This is intentional to prevent:

Hanging processes in automated environments
Resource conflicts in CI/CD pipelines
Interactive browser windows in headless environments

CONSOLE.LOG CAPTURE PATTERN: The tool follows the pattern established in ci/wasm_test.py and ci/ci/scrapers/:

// Example captured console.log patterns:
[14:25:30] log: FastLED_onFrame called: {"frame":1,"leds":100}
[14:25:30] log: Audio worklet initialized
[14:25:31] error: Missing audio_worklet_processor.js
[14:25:31] warning: WebGL context lost

INTEGRATION WITH EXISTING CI:

Complements existing ci/wasm_test.py functionality
Uses same playwright patterns as ci/ci/scrapers/
Leverages existing pyproject.toml dependencies
Compatible with existing Docker-based compilation workflow

Project Structure

src/ - Main FastLED library source code
examples/ - Arduino examples demonstrating FastLED usage
tests/ - Test files and infrastructure
ci/ - Continuous integration scripts
docs/ - Documentation

Key Commands

uv run test.py - Run all tests
uv run test.py --cpp - Run C++ tests only
uv run test.py TestName - Run specific C++ test
- For example: running test_xypath.cpp would be uv run test.py xypath
./lint - Run code formatting/linting
uv run ci/ci-compile.py uno --examples Blink - Compile examples for specific platform
- For example (uno): uv run ci/ci-compile.py uno --examples Blink
- For example (esp32dev): uv run ci/ci-compile.py esp32dev --examples Blink
- For example (esp8266): uv run ci/ci-compile.py esp01 --examples Blink
- For example (teensy31): uv run ci/ci-compile.py teensy31 --examples Blink
WASM Compilation - Compile Arduino sketches to run in web browsers:
- uv run ci/wasm_compile.py examples/Blink -b --open - Compile Blink to WASM and open browser
- uv run ci/wasm_compile.py path/to/your/sketch -b --open - Compile any sketch to WASM
Symbol Analysis - Analyze binary size and optimization opportunities:
- uv run ci/ci/symbol_analysis.py --board uno - Analyze UNO platform
- uv run ci/ci/symbol_analysis.py --board esp32dev - Analyze ESP32 platform
- uv run ci/demo_symbol_analysis.py - Analyze all available platforms

🤖 AI AGENT LINTING GUIDELINES

FOREGROUND AGENTS (Interactive Development)

🚨 ALWAYS USE bash lint - DO NOT RUN INDIVIDUAL LINTING SCRIPTS

✅ CORRECT: bash lint
❌ FORBIDDEN: ./lint-js, ./check-js, python3 scripts/enhance-js-typing.py
❌ FORBIDDEN: uv run ruff check, uv run black, individual tools

WHY: bash lint provides:

Comprehensive coverage - Python, C++, JavaScript, and enhancement analysis
Consistent workflow - Single command for all linting needs
Proper sequencing - Runs tools in the correct order with dependencies
Clear output - Organized sections showing what's being checked
Agent guidance - Shows proper usage for AI agents

BACKGROUND AGENTS (Automated/CI Environments)

CAN USE FINE-GRAINED LINTING FOR SPECIFIC NEEDS

Background agents may use individual linting scripts when needed:

./lint-js - JavaScript-only linting
./check-js - JavaScript type checking
python3 scripts/enhance-js-typing.py - JavaScript enhancement analysis
uv run ruff check - Python linting only
MCP server lint_code tool - Programmatic access

BUT STILL PREFER bash lint FOR COMPREHENSIVE CHECKING

Linting Script Integration

The bash lint command now includes:

📝 Python Linting - ruff, black, isort, pyright
🔧 C++ Linting - clang-format (when enabled)
🌐 JavaScript Linting - Deno lint, format check, type checking
🔍 JavaScript Enhancement - Analysis and recommendations
💡 AI Agent Guidance - Clear instructions for proper usage

When to Use Individual Scripts

FOREGROUND AGENTS: Never. Always use bash lint.

BACKGROUND AGENTS: Only when:

Debugging specific issues with one language/tool
Testing incremental changes to linting configuration
Running targeted analysis for specific files
Integrating with automated workflows via MCP server

Development Guidelines

Follow existing code style and patterns
Run tests before committing changes
Use the MCP server tools for common tasks
Check examples when making API changes

🚨 CRITICAL: .INO FILE CREATION RULES 🚨

⚠️ THINK BEFORE CREATING .INO FILES ⚠️

.ino files should be created SPARINGLY and ONLY when truly justified.

🚫 WHEN NOT TO CREATE .INO FILES:

Testing minor code changes - Use existing test files or unit tests
Quick API validation - Use unit tests or modify existing examples
Debugging specific functions - Use test files, not new sketches
One-off experiments - Create temporary test files instead
Small feature tests - Extend existing relevant examples

✅ WHEN TO CREATE .INO FILES:

1. Temporary Testing (.ino)

Use Pattern: temp_<feature>.ino or test_<api>.ino

// temp_json_api.ino - Testing new JSON fetch functionality
// test_networking.ino - Validating network stack changes

✅ FOR: Testing new APIs during development
✅ FOR: Quick prototyping and validation
✅ DELETE AFTER USE - These are temporary by design

2. Significant New Feature Examples

Use Pattern: examples/<FeatureName>/<FeatureName>.ino

// examples/JsonFetchApi/JsonFetchApi.ino - Comprehensive JSON API example
// examples/NetworkStack/NetworkStack.ino - Major networking features

✅ FOR: Large, comprehensive new features
✅ FOR: APIs that warrant dedicated examples
✅ FOR: Features that users will commonly implement
✅ PERMANENT - These become part of the example library

📋 CREATION CHECKLIST:

Before creating ANY .ino file, ask:

🤔 Is this testing a new API?
- YES → Create temp_<name>.ino, delete after testing
- NO → Consider alternatives
🤔 Is this a significant new feature that users will commonly use?
- YES → Create examples/<FeatureName>/<FeatureName>.ino
- NO → Use existing examples or test files
🤔 Can I modify an existing example instead?
- YES → Extend existing example rather than creating new
- NO → Proceed with creation
🤔 Is this just for debugging/validation?
- YES → Use unit tests or temporary test files
- NO → Consider if it meets the "significant feature" criteria

🔍 REVIEW CRITERIA:

For Feature Examples (.ino files that stay):

✅ Demonstrates complete, real-world usage patterns
✅ Covers multiple aspects of the feature comprehensively
✅ Provides educational value for users
✅ Shows best practices and common use cases
✅ Is likely to be referenced by multiple users

For Temporary Testing (.ino files that get deleted):

✅ Clearly named as temporary (temp_, test_)
✅ Focused on specific API validation
✅ Will be deleted after development cycle
✅ Too complex for unit test framework

❌ EXAMPLES OF WHAT NOT TO CREATE:

test_basic_led.ino - Use existing Blink example
debug_colors.ino - Use existing ColorPalette example
quick_brightness.ino - Use unit tests or modify existing example
validate_pins.ino - Use PinTest example or unit tests

✅ EXAMPLES OF JUSTIFIED CREATIONS:

temp_new_wifi_api.ino - Testing major new WiFi functionality (temporary)
examples/MachineLearning/MachineLearning.ino - New ML integration feature (permanent)
temp_performance_test.ino - Validating optimization changes (temporary)

🧹 CLEANUP RESPONSIBILITY:

Temporary files: Creator must delete when testing is complete
Feature examples: Must be maintained and updated as API evolves
Abandoned files: Regular cleanup reviews to remove unused examples

Remember: The examples directory is user-facing documentation. Every .ino file should provide clear value to FastLED users.

Memory Management with Smart Pointers and Moveable Objects

🚨 CRITICAL: Always use proper RAII patterns - smart pointers, moveable objects, or wrapper classes instead of raw pointers for resource management.

Resource Management Options:

✅ PREFERRED: fl::shared_ptr<T> for shared ownership (multiple references to same object)
✅ PREFERRED: fl::unique_ptr<T> for exclusive ownership (single owner, automatic cleanup)
✅ PREFERRED: Moveable wrapper objects (like fl::promise<T>) for safe copying and transferring of unique resources
✅ ACCEPTABLE: fl::vector<T> storing objects by value when objects support move/copy semantics
❌ AVOID: fl::vector<T*> storing raw pointers - use fl::vector<fl::shared_ptr<T>> or fl::vector<fl::unique_ptr<T>>
❌ AVOID: Manual new/delete - use fl::make_shared<T>() or fl::make_unique<T>()

Moveable Wrapper Pattern: When you have a unique resource (like a future, file handle, or network connection) that needs to be passed around easily, create a moveable wrapper class that:

Internally manages the unique resource (often with fl::unique_ptr<T> or similar)
Provides copy semantics through shared implementation details
Maintains clear ownership semantics
Allows safe transfer between contexts

Examples:

// ✅ GOOD - Using smart pointers
fl::vector<fl::shared_ptr<HttpClient>> mActiveClients;
auto client = fl::make_shared<HttpClient>();
mActiveClients.push_back(client);

// ✅ GOOD - Using unique_ptr for exclusive ownership
fl::unique_ptr<HttpClient> client = fl::make_unique<HttpClient>();

// ✅ GOOD - Moveable wrapper objects (fl::promise example)
fl::vector<fl::promise<Response>> mActivePromises;  // Copyable wrapper around unique future
fl::promise<Response> promise = fetch.get(url).execute();
mActivePromises.push_back(promise);  // Safe copy, shared internal state

// ✅ GOOD - Objects stored by value (if copyable/moveable)
fl::vector<Request> mRequests;  // When Request supports copy/move

// ❌ BAD - Raw pointers require manual memory management
fl::vector<Promise*> mActivePromises;  // Memory leaks possible
Promise* promise = new Promise();      // Who calls delete?

fl::promise as Moveable Wrapper Example:

// fl::promise<T> wraps a unique fl::future<T> but provides copyable semantics
class promise<T> {
    fl::shared_ptr<future<T>> mImpl;  // Shared wrapper around unique resource
public:
    promise(const promise& other) : mImpl(other.mImpl) {}  // Safe copying
    promise(promise&& other) : mImpl(fl::move(other.mImpl)) {}  // Move support
    // ... wrapper delegates to internal future
};

// Usage - can be copied and passed around safely
fl::promise<Response> promise = http_get_promise("https://api.example.com");
someContainer.push_back(promise);  // Copy is safe
processAsync(promise);  // Can pass to multiple places

Why This Pattern:

Automatic cleanup - No memory leaks from forgotten delete calls
Exception safety - Resources automatically freed even if exceptions occur
Clear ownership - Code clearly shows who owns what objects
Thread safety - Smart pointers provide atomic reference counting
Easy sharing - Moveable wrappers allow safe copying of unique resources
API flexibility - Can pass resources between different contexts safely

🔧 CMAKE BUILD SYSTEM ARCHITECTURE (DEPRECATED - NO LONGER USED)

⚠️ IMPORTANT: CMake build system is no longer used. FastLED now uses a Python-based build system.

Build System Overview (Historical Reference)

FastLED previously used a sophisticated CMake build system located in tests/cmake/ with modular configuration:

Core Build Files:

tests/CMakeLists.txt - Main CMake entry point
tests/cmake/ - Modular CMake configuration directory

Key CMake Modules:

LinkerCompatibility.cmake - 🚨 CRITICAL for linker issues - GNU↔MSVC flag translation, lld-link compatibility, warning suppression
CompilerDetection.cmake - Compiler identification and toolchain setup
CompilerFlags.cmake - Compiler-specific flag configuration
DebugSettings.cmake - Debug symbol and optimization configuration
OptimizationSettings.cmake - LTO and performance optimization settings
ParallelBuild.cmake - Parallel compilation and linker selection (mold, lld)
TestConfiguration.cmake - Test target setup and configuration
BuildOptions.cmake - Build option definitions and defaults

Linker Configuration (Most Important for Build Issues)

🎯 PRIMARY LOCATION for linker problems: tests/cmake/LinkerCompatibility.cmake

Key Functions:

apply_linker_compatibility() - Main entry point - auto-detects lld-link and applies compatibility
translate_gnu_to_msvc_linker_flags() - Converts GNU-style flags to MSVC-style for lld-link
get_dead_code_elimination_flags() - Platform-specific dead code elimination
get_debug_flags() - Debug information configuration
get_optimization_flags() - Performance optimization flags

Linker Detection Logic:

if(WIN32 AND CMAKE_CXX_COMPILER_ID MATCHES "Clang")
    find_program(LLDLINK_EXECUTABLE lld-link)
    if(LLDLINK_EXECUTABLE)
        # Apply lld-link compatibility automatically
    endif()
endif()

Common Linker Issues & Solutions:

lld-link warnings: Suppressed via /ignore:4099 in apply_linker_compatibility()
GNU→MSVC flag translation: Automatic in translate_gnu_to_msvc_linker_flags()
Dead code elimination: Platform-specific via get_dead_code_elimination_flags()
Debug symbol conflicts: Handled in get_debug_flags()

Compiler Configuration

Compiler Detection: tests/cmake/CompilerDetection.cmake

Auto-detects Clang, GCC, MSVC
Sets up toolchain-specific configurations
Handles cross-compilation scenarios

Compiler Flags: tests/cmake/CompilerFlags.cmake

Warning configurations per compiler
Optimization level management
Platform-specific adjustments

Build Options & Configuration

Available Build Options (defined in BuildOptions.cmake):

FASTLED_DEBUG_LEVEL - Debug information level (NONE, MINIMAL, STANDARD, FULL)
FASTLED_OPTIMIZATION_LEVEL - Optimization (O0, O1, O2, O3, Os, Ofast)
FASTLED_ENABLE_LTO - Link-time optimization
FASTLED_ENABLE_PARALLEL_BUILD - Parallel compilation
FASTLED_STATIC_RUNTIME - Static runtime linking

Testing Infrastructure

Test Configuration: tests/cmake/TestConfiguration.cmake

Defines test targets and dependencies
Configures test execution parameters
Sets up coverage and profiling

Test Execution:

bash test - Comprehensive test runner (preferred)
uv run test.py - Python test interface
Individual test executables in .build/bin/

Build Troubleshooting Guide

For Linker Issues:

Check tests/cmake/LinkerCompatibility.cmake first
Look for lld-link detection and compatibility functions
Check GNU→MSVC flag translation logic
Verify warning suppression settings

For Compiler Issues:

Check tests/cmake/CompilerDetection.cmake for detection logic
Review tests/cmake/CompilerFlags.cmake for flag conflicts
Verify optimization settings in OptimizationSettings.cmake

For Build Performance:

Check tests/cmake/ParallelBuild.cmake for parallel settings
Review LTO configuration in OptimizationSettings.cmake
Verify linker selection (mold, lld, default)

🚨 CRITICAL REQUIREMENTS FOR ALL AGENTS (FOREGROUND & BACKGROUND) 🚨

🚨 MANDATORY COMMAND EXECUTION RULES 🚨

FOREGROUND AGENTS (Interactive Development)

FOREGROUND AGENTS MUST FOLLOW THESE COMMAND EXECUTION PATTERNS:

Python Code Execution:

❌ NEVER run Python code directly
✅ ALWAYS create/modify tmp.py with your code
✅ ALWAYS run: uv run tmp.py

Shell Command Execution:

❌ NEVER run shell commands directly
✅ ALWAYS create/modify tmp.sh with your commands
✅ ALWAYS run: bash tmp.sh

Command Execution Examples:

Python Code Pattern:

# tmp.py
import subprocess
result = subprocess.run(['git', 'status'], capture_output=True, text=True)
print(result.stdout)

Then run: uv run tmp.py

Shell Commands Pattern:

# tmp.sh
#!/bin/bash
git status
ls -la
uv run ci/ci-compile.py uno --examples Blink

Then run: bash tmp.sh

BACKGROUND AGENTS (Automated/CI Environments)

BACKGROUND AGENTS MUST FOLLOW THESE RESTRICTED COMMAND EXECUTION PATTERNS:

Python Code Execution:

❌ NEVER run Python code directly
❌ NEVER create/use tmp.py files (forbidden for background agents)
✅ ALWAYS use uv run with existing scripts (e.g., uv run test.py, uv run ci/ci-compile.py)
✅ ALWAYS use MCP server tools for programmatic operations when available

Shell Command Execution:

❌ NEVER run shell commands directly
❌ NEVER create/use tmp.sh files (forbidden for background agents)
✅ ALWAYS use existing bash scripts (e.g., bash test, bash lint)
✅ ALWAYS use uv run for Python scripts with proper arguments
✅ ALWAYS use MCP server tools for complex operations when available

Background Agent Command Examples:

✅ ALLOWED - Using existing scripts:

bash test
bash lint
uv run test.py audio_json_parsing
uv run ci/ci-compile.py uno --examples Blink

❌ FORBIDDEN - Creating temporary files:

# DON'T DO THIS - tmp.sh is forbidden for background agents
echo "git status" > tmp.sh
bash tmp.sh

✅ PREFERRED - Using MCP server tools:

uv run mcp_server.py
# Then use appropriate MCP tools like: validate_completion, symbol_analysis, etc.

DELETE Operations - DANGER ZONE (ALL AGENTS):

🚨 STOP and ask for permission before ANY delete operations
✅ EXCEPTION: Single files that you just created are OK to delete
❌ NEVER delete multiple files without explicit permission
❌ NEVER delete directories without explicit permission
❌ NEVER delete system files or project files without permission

Git-Bash Terminal Truncation Issue

🚨 IMPORTANT: Git-Bash terminal may truncate the first character of commands

Problem: The git-bash terminal on Windows sometimes truncates the first character of commands, causing them to fail or execute incorrectly.

Solution: Pre-pend commands with an additional space when using git-bash:

✅ CORRECT: bash test (note the leading space)
❌ INCORRECT: bash test (may get truncated to ash test)

Examples:

# Good - with leading space for git-bash compatibility
 bash test
 uv run test.py
 bash lint

# Bad - may get truncated in git-bash
bash test
uv run test.py
bash lint

Why: This ensures commands work reliably across all terminal environments, especially git-bash on Windows systems.

Why These Rules Exist:

Ensures all operations are reviewable and traceable
Prevents accidental destructive operations in automated environments
Allows for better debugging and error handling
Maintains consistency across different agent types
Provides audit trail for all system modifications
Prevents background agents from creating unnecessary temporary files

These command execution rules apply to ALL operations including but not limited to:

File system operations (creating, modifying, deleting files)
Git operations (commits, pushes, branch changes)
Package installations and updates
Build and compilation commands
Test execution and validation
System configuration changes

MANDATORY MEMORY REFRESH BEFORE COMPLETION

🚨 ALL AGENTS MUST REFRESH THEIR MEMORY BEFORE CONCLUDING WORK:

The AI shall read the cursor rules again to find out what to do before task is considered complete
- This is MANDATORY for both foreground and background agents
- Reading the cursor rules refreshes your memory about the latest project rules, coding standards, and requirements
- This ensures you have current information about testing procedures, validation tools, and completion requirements
- Do NOT indicate your work is "done" until you have refreshed your memory by reading the cursor rules

🚨 CRITICAL REQUIREMENTS FOR BACKGROUND AGENTS 🚨

MANDATORY PRE-COMPLETION VALIDATION

ALL BACKGROUND AGENTS MUST FOLLOW THESE REQUIREMENTS BEFORE INDICATING COMPLETION:

🚨 ALWAYS RUN bash test BEFORE INDICATING COMPLETION
- This is MANDATORY and NON-NEGOTIABLE for all background agents
- The command bash test runs the full test suite including unit tests and compilation checks
- Background agents MUST NOT indicate they are "done" until ALL tests pass
🚨 USE MCP SERVER VALIDATION TOOL
- Use the validate_completion tool from the MCP server: uv run mcp_server.py
- This tool runs bash test and validates that all tests pass
- Only indicate completion if this validation tool returns success
🚨 ZERO TOLERANCE FOR TEST FAILURES
- If ANY test fails, the background agent MUST fix the issues before completion
- Do NOT indicate completion with failing tests
- Do NOT ignore test errors or warnings

Background Agent Completion Checklist:

All code changes have been made
bash test has been run and ALL tests pass
No compilation errors or warnings
MCP server validate_completion tool shows success
Only then indicate task completion

FAILURE TO FOLLOW THESE REQUIREMENTS WILL RESULT IN BROKEN CODE SUBMISSIONS.

C++ Design Patterns

Shared Implementation Pattern: When writing a lot of code that applies the same operation on a bunch of C++ objects, try and determine if those objects share a common base class or internal object. If so consider whether it's appropriate to move the implementation into a shared space.

Code Standards

Avoid std:: Prefixed Functions

DO NOT use std:: prefixed functions or headers in the codebase. This project provides its own STL-equivalent implementations under the fl:: namespace.

Examples of what to avoid and use instead:

Headers:

Core Language Support:

❌ #include <type_traits> → ✅ #include "fl/type_traits.h"
❌ #include <algorithm> → ✅ #include "fl/algorithm.h"
❌ #include <functional> → ✅ #include "fl/functional.h"
❌ #include <initializer_list> → ✅ #include "fl/initializer_list.h"

Containers:

❌ #include <vector> → ✅ #include "fl/vector.h"
❌ #include <map> → ✅ #include "fl/map.h"
❌ #include <unordered_map> → ✅ #include "fl/hash_map.h"
❌ #include <unordered_set> → ✅ #include "fl/hash_set.h"
❌ #include <set> → ✅ #include "fl/set.h"
❌ #include <span> → ✅ #include "fl/slice.h"

Utilities & Smart Types:

❌ #include <optional> → ✅ #include "fl/optional.h"
❌ #include <variant> → ✅ #include "fl/variant.h"
❌ #include <utility> → ✅ #include "fl/pair.h" (for std::pair)
❌ #include <string> → ✅ #include "fl/string.h"
❌ #include <memory> → ✅ #include "fl/scoped_ptr.h" or #include "fl/ptr.h"

Stream/IO:

❌ #include <sstream> → ✅ #include "fl/sstream.h"

Threading:

❌ #include <thread> → ✅ #include "fl/thread.h"

Math & System:

❌ #include <cmath> → ✅ #include "fl/math.h"
❌ #include <cstdint> → ✅ #include "fl/stdint.h"

Functions and classes:

❌ std::move() → ✅ fl::move()
❌ std::forward() → ✅ fl::forward()
❌ std::vector → ✅ fl::vector
❌ std::enable_if → ✅ fl::enable_if

Why: The project maintains its own implementations to ensure compatibility across all supported platforms and to avoid bloating the library with unnecessary STL dependencies.

Before using any standard library functionality, check if there's a fl:: equivalent in the src/fl/ directory first.

Compiler Warning Suppression

ALWAYS use the FastLED compiler control macros from fl/compiler_control.h for warning suppression. This ensures consistent cross-compiler support and proper handling of platform differences.

Correct Warning Suppression Pattern:

#include "fl/compiler_control.h"

// Suppress specific warning around problematic code
FL_DISABLE_WARNING_PUSH
FL_DISABLE_FORMAT_TRUNCATION  // Use specific warning macros
// ... code that triggers warnings ...
FL_DISABLE_WARNING_POP

Available Warning Suppression Macros:

✅ FL_DISABLE_WARNING_PUSH / FL_DISABLE_WARNING_POP - Standard push/pop pattern
✅ FL_DISABLE_WARNING(warning_name) - Generic warning suppression (use sparingly)
✅ FL_DISABLE_WARNING_GLOBAL_CONSTRUCTORS - Clang global constructor warnings
✅ FL_DISABLE_WARNING_SELF_ASSIGN_OVERLOADED - Clang self-assignment warnings
✅ FL_DISABLE_FORMAT_TRUNCATION - GCC format truncation warnings

What NOT to do:

❌ NEVER use raw #pragma directives - they don't handle compiler differences
❌ NEVER write manual #ifdef __clang__ / #ifdef __GNUC__ blocks - use the macros
❌ NEVER ignore warnings without suppression - fix the issue or suppress appropriately

Examples:

// ✅ CORRECT - Using FastLED macros
#include "fl/compiler_control.h"

FL_DISABLE_WARNING_PUSH
FL_DISABLE_FORMAT_TRUNCATION
// Code that triggers format truncation warnings
sprintf(small_buffer, "Very long format string %d", value);
FL_DISABLE_WARNING_POP

// ❌ INCORRECT - Raw pragma directives
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wformat-truncation"
sprintf(small_buffer, "Very long format string %d", value);
#pragma GCC diagnostic pop

Why: The FastLED compiler control system automatically handles:

Compiler detection (GCC vs Clang vs MSVC)
Version compatibility (warnings that don't exist on older compilers)
Platform specifics (AVR, ESP32, ARM, etc.)
Consistent naming across different compiler warning systems

Debug Printing

Use FL_WARN for debug printing throughout the codebase. This ensures consistent debug output that works in both unit tests and live application testing.

Usage:

✅ FL_WARN("Debug message: " << message);
❌ FL_WARN("Value: %d", value);

Why: FL_WARN provides a unified logging interface that works across all platforms and testing environments, including unit tests and Arduino sketches.

Emoticon and Emoji Usage Policy

NO emoticons or emoji characters are allowed in C++ source files. This ensures professional, maintainable code that works correctly across all platforms and development environments.

Prohibited in C++ Files:

❌ C++ source files (*.cpp, *.c)
❌ C++ header files (*.h, *.hpp)
❌ Comments in C++ files - use clear text instead
❌ String literals in C++ code - use descriptive text
❌ Log messages in C++ code - use text prefixes like "SUCCESS:", "ERROR:", "WARNING:"

Examples of what NOT to do in C++ files:

// ❌ BAD - Emoticons in comments
// 🎯 This function handles user input

// ❌ BAD - Emoticons in log messages  
FL_WARN("✅ Operation successful!");
FL_WARN("❌ Error occurred: " << error_msg);

// ❌ BAD - Emoticons in string literals
const char* status = "🔄 Processing...";

Examples of correct alternatives in C++ files:

// ✅ GOOD - Clear text in comments
// TUTORIAL: This function handles user input

// ✅ GOOD - Text prefixes in log messages
FL_WARN("SUCCESS: Operation completed successfully!");
FL_WARN("ERROR: Failed to process request: " << error_msg);

// ✅ GOOD - Descriptive text in string literals  
const char* status = "PROCESSING: Request in progress...";

Allowed in Python Files:

✅ Python source files (*.py) - emoticons are acceptable for build scripts, tools, and utilities
✅ Python comments and docstrings - can use emoticons for clarity in development tools
✅ Python log messages - emoticons OK in build/test output for visual distinction

Why:

Cross-platform compatibility - Some compilers/platforms have issues with Unicode characters
Professional codebase - Maintains serious, enterprise-grade appearance
Accessibility - Screen readers and text-based tools work better with plain text
Consistency - Ensures uniform code style across all C++ files
Debugging - Text-based prefixes are easier to search and filter in logs

Before adding any visual indicators to C++ code, use text-based alternatives like "TODO:", "NOTE:", "WARNING:", "SUCCESS:", "ERROR:" prefixes.

Naming Conventions

Follow these naming conventions for consistency across the codebase:

Simple Objects:

✅ Use lowercase class names for simple objects (e.g., fl::vec2f, fl::point, fl::rect)
❌ Avoid: fl::Vec2f, fl::Point, fl::Rect

Complex Objects:

✅ Use CamelCase with uppercase first character for complex objects (e.g., Raster, Controller, Canvas)
❌ Avoid: raster, controller, canvas

Pixel Types:

✅ Use ALL CAPS for pixel types (e.g., CRGB, CHSV, HSV16, RGB24)
❌ Avoid: crgb, Crgb, chsv, Chsv

Member Variables and Functions:

Complex Classes/Objects:

✅ Member variables: Use mVariableName format (e.g., mPixelCount, mBufferSize, mCurrentIndex)
✅ Member functions: Use camelCase (e.g., getValue(), setPixelColor(), updateBuffer())
❌ Avoid: m_variable_name, variableName, GetValue(), set_pixel_color()

Simple Classes/Structs:

✅ Member variables: Use lowercase snake_case (e.g., x, y, width, height, pixel_count)
✅ Member functions: Use camelCase (e.g., getValue(), setPosition(), normalize())
❌ Avoid: mX, mY, get_value(), set_position()

Examples:

// Complex class - use mVariableName for members
class Controller {
private:
    int mPixelCount;           // ✅ Complex class member variable
    uint8_t* mBuffer;          // ✅ Complex class member variable
    bool mIsInitialized;       // ✅ Complex class member variable
    
public:
    void setPixelCount(int count);  // ✅ Complex class member function
    int getPixelCount() const;      // ✅ Complex class member function
    void updateBuffer();            // ✅ Complex class member function
};

// Simple struct - use snake_case for members
struct vec2 {
    int x;                     // ✅ Simple struct member variable
    int y;                     // ✅ Simple struct member variable
    
    float magnitude() const;   // ✅ Simple struct member function
    void normalize();          // ✅ Simple struct member function
};

struct point {
    float x;                   // ✅ Simple struct member variable
    float y;                   // ✅ Simple struct member variable
    float z;                   // ✅ Simple struct member variable
    
    void setPosition(float x, float y, float z);  // ✅ Simple struct member function
    float distanceTo(const point& other) const;   // ✅ Simple struct member function
};

Why: These conventions help distinguish between different categories of objects and maintain consistency with existing FastLED patterns. Complex classes use Hungarian notation for member variables to clearly distinguish them from local variables, while simple structs use concise snake_case for lightweight data containers.

Container Parameter Types

Prefer fl::span<T> over fl::vector<T> or arrays for function parameters. fl::span<T> provides a non-owning view that automatically converts from various container types, making APIs more flexible and efficient.

Examples:

✅ void processData(fl::span<const uint8_t> data) - accepts arrays, vectors, and other containers
❌ void processData(fl::vector<uint8_t>& data) - only accepts fl::Vector
❌ void processData(uint8_t* data, size_t length) - requires manual length tracking

Benefits:

Automatic conversion: fl::span<T> can automatically convert from fl::vector<T>, C-style arrays, and other container types
Type safety: Maintains compile-time type checking while being more flexible than raw pointers
Performance: Zero-cost abstraction that avoids unnecessary copying or allocation
Consistency: Provides a uniform interface for working with contiguous data

When to use fl::vector<T> instead:

When you need ownership and dynamic resizing capabilities
When storing data as a class member that needs to persist

Why: Using fl::span<T> for parameters makes functions more reusable and avoids forcing callers to convert their data to specific container types.

Exception Handling

DO NOT use try-catch blocks or C++ exception handling in the codebase. FastLED is designed to work on embedded systems like Arduino where exception handling may not be available or desired due to memory and performance constraints.

Examples of what to avoid and use instead:

Avoid Exception Handling:

❌ try { ... } catch (const std::exception& e) { ... } - Exception handling not available on many embedded platforms
❌ throw std::runtime_error("error message") - Throwing exceptions not supported
❌ #include <exception> or #include <stdexcept> - Exception headers not needed

Use Error Handling Alternatives:

✅ Return error codes: bool function() { return false; } or custom error enums
✅ Optional types: fl::optional<T> for functions that may not return a value
✅ Assertions: FL_ASSERT(condition) for debug-time validation
✅ Early returns: if (!valid) return false; for error conditions
✅ Status objects: Custom result types that combine success/failure with data

Examples of proper error handling:

// Good: Using return codes
bool initializeHardware() {
    if (!setupPins()) {
        FL_WARN("Failed to setup pins");
        return false;
    }
    return true;
}

// Good: Using fl::optional
fl::optional<float> calculateValue(int input) {
    if (input < 0) {
        return fl::nullopt;  // No value, indicates error
    }
    return fl::make_optional(sqrt(input));
}

// Good: Using early returns
void processData(const uint8_t* data, size_t len) {
    if (!data || len == 0) {
        FL_WARN("Invalid input data");
        return;  // Early return on error
    }
    // Process data...
}

Why: Many embedded platforms (especially Arduino-compatible boards) don't support C++ exceptions or have them disabled to save memory and improve performance. FastLED must work reliably across all supported platforms.

JSON Usage - Ideal API Patterns

🎯 PREFERRED: Use the modern fl::Json class for all JSON operations. FastLED provides an ideal JSON API that prioritizes type safety, ergonomics, and crash-proof operation.

✅ IDIOMATIC JSON USAGE:

// NEW: Clean, safe, idiomatic API
fl::Json json = fl::Json::parse(jsonStr);
int brightness = json["config"]["brightness"] | 128;  // Gets value or 128 default
string name = json["device"]["name"] | string("default");  // Type-safe with default
bool enabled = json["features"]["networking"] | false;  // Never crashes

// Array operations
if (json["effects"].contains("rainbow")) {
    // Safe array checking
}

❌ DISCOURAGED: Verbose legacy API:

// OLD: Verbose, error-prone API (still works, but not recommended)
fl::JsonDocument doc;
fl::string error;
fl::parseJson(jsonStr, &doc, &error);
int brightness = doc["config"]["brightness"].as<int>();  // Can crash if missing

Key Benefits of Ideal API:

🛡️ Type Safety - No crashes on missing fields or type mismatches
🎯 Default Values - Clean json["key"] | default syntax
📖 Readable Code - 50% less boilerplate for common operations
🚀 Testing - Easy test data construction with JsonBuilder

📚 Reference Example: See examples/Json/Json.ino for comprehensive usage patterns and API comparison.

Testing with JsonBuilder:

// Easy test data construction
auto json = JsonBuilder()
    .set("brightness", 128)
    .set("enabled", true)
    .set("name", "test_device")
    .build();

// Type-safe testing
CHECK_EQ(json["brightness"] | 0, 128);
CHECK(json["enabled"] | false);

🎯 GUIDELINE: Always prefer the ideal fl::Json API for new code. The legacy fl::parseJson API remains available for backward compatibility but should be avoided in new implementations.

⚠️ CRITICAL WARNING: C++ ↔ JavaScript Bindings

🚨 EXTREMELY IMPORTANT: DO NOT MODIFY FUNCTION SIGNATURES IN WEBASSEMBLY BINDINGS WITHOUT EXTREME CAUTION! 🚨

The FastLED project includes WebAssembly (WASM) bindings that bridge C++ and JavaScript code. Changing function signatures in these bindings is a major source of runtime errors and build failures.

Key Binding Files (⚠️ HIGH RISK ZONE ⚠️):

src/platforms/wasm/js_bindings.cpp - Main JavaScript interface via EM_ASM
src/platforms/wasm/ui.cpp - UI update bindings with extern "C" wrappers
src/platforms/wasm/active_strip_data.cpp - Strip data bindings via EMSCRIPTEN_BINDINGS
src/platforms/wasm/fs_wasm.cpp - File system bindings via EMSCRIPTEN_BINDINGS

Before Making ANY Changes to These Files:

🛑 STOP and consider if the change is absolutely necessary
📖 Read the warning comments at the top of each binding file
🧪 Test extensively on WASM target after any changes
🔗 Verify both C++ and JavaScript sides remain synchronized
📝 Update corresponding JavaScript code if function signatures change

Common Binding Errors:

Parameter type mismatches (e.g., const char* vs std::string)
Return type changes that break JavaScript expectations
Function name changes without updating JavaScript calls
Missing extern "C" wrappers for EMSCRIPTEN_KEEPALIVE functions
EMSCRIPTEN_BINDINGS macro changes without updating JS Module calls

If You Must Modify Bindings:

Update BOTH sides simultaneously (C++ and JavaScript)
Maintain backward compatibility when possible
Add detailed comments explaining the interface contract
Test thoroughly with real WASM builds, not just compilation
Update documentation and interface specs

Remember: The bindings are a CONTRACT between C++ and JavaScript. Breaking this contract causes silent failures and mysterious bugs that are extremely difficult to debug.

🚨 WASM PLATFORM SPECIFIC RULES 🚨

WASM Unified Build Awareness

🚨 CRITICAL: WASM builds use unified compilation when FASTLED_ALL_SRC=1 is enabled (automatic for Clang builds)

Root Cause: Multiple .cpp files are compiled together in a single compilation unit, causing:

Duplicate function definitions
Type signature conflicts
Symbol redefinition errors

MANDATORY RULES:

ALWAYS check for unified builds when modifying WASM platform files
NEVER create duplicate function definitions across WASM .cpp files
USE EMSCRIPTEN_KEEPALIVE functions as canonical implementations
MATCH Emscripten header signatures exactly for external C functions
REMOVE conflicting implementations and add explanatory comments

Fix Pattern Example:

// In timer.cpp (CANONICAL)
extern "C" {
EMSCRIPTEN_KEEPALIVE uint32_t millis() {
    // Implementation
}
}

// In js.cpp (FIXED)
extern "C" {
// NOTE: millis() and micros() functions are defined in timer.cpp with EMSCRIPTEN_KEEPALIVE  
// to avoid duplicate definitions in unified builds
}

WASM Async Platform Pump Pattern

🚨 CRITICAL: Avoid long blocking sleeps that prevent responsive async processing

MANDATORY RULES:

AVOID long blocking sleeps (e.g., emscripten_sleep(100)) in main loops
USE short sleep intervals (1ms) for responsive yielding in main loops
ALLOW JavaScript to control timing via extern functions rather than blocking C++ loops

Correct Implementation:

// ✅ GOOD - responsive yielding without blocking
while (true) {
    // Keep pthread alive for extern function calls
    // Use short sleep for responsiveness
    emscripten_sleep(1);    // 1ms yield for responsiveness
}

Why This Matters:

Long blocking sleeps prevent responsive browser interaction
JavaScript should control FastLED timing via requestAnimationFrame
Short sleep intervals maintain responsiveness while allowing other threads to work

WASM Function Signature Matching

🚨 CRITICAL: External C function declarations must match Emscripten headers exactly

Common Error Pattern:

// ❌ WRONG - causes compilation error
extern "C" void emscripten_sleep(int ms);

// ✅ CORRECT - matches official Emscripten header  
extern "C" void emscripten_sleep(unsigned int ms);

MANDATORY RULES:

ALWAYS verify against official Emscripten header signatures
NEVER assume parameter types - check the actual headers
UPDATE signatures immediately when compilation errors occur

WASM Sketch Compilation

🎯 HOW TO COMPILE ANY ARDUINO SKETCH TO WASM:

Basic Compilation Commands:

# Compile any sketch directory to WASM
uv run ci/wasm_compile.py path/to/your/sketch

# Compile with build and open browser automatically
uv run ci/wasm_compile.py path/to/your/sketch -b --open

# Compile examples/Blink to WASM
uv run ci/wasm_compile.py examples/Blink -b --open

# Compile examples/DemoReel100 to WASM  
uv run ci/wasm_compile.py examples/DemoReel100 -b --open

Output: Creates fastled_js/ folder with:

fastled.js - JavaScript loader
fastled.wasm - WebAssembly binary
index.html - HTML page to run the sketch

Run in Browser:

# Simple HTTP server to test
cd fastled_js
python -m http.server 8000
# Open http://localhost:8000

🚨 REQUIREMENTS:

Docker must be installed and running
Internet connection (for Docker image download on first run)
~1GB RAM for Docker container during compilation

WASM Testing Requirements

🚨 MANDATORY: Always test WASM compilation after platform file changes

Platform Testing Commands:

# Test WASM platform changes (for platform developers)
uv run ci/wasm_compile.py -b examples/wasm

# Quick test without full build
uv run ci/wasm_compile.py examples/wasm --quick

Watch For These Error Patterns:

error: conflicting types for 'function_name'
error: redefinition of 'function_name'
warning: attribute declaration must precede definition
RuntimeError: unreachable (often async-related)

MANDATORY RULES:

ALWAYS test WASM compilation after modifying any WASM platform files
USE uv run ci/wasm_compile.py for validation
WATCH for unified build conflicts in compilation output
VERIFY async operations work properly in browser environment

WASM Platform File Organization

Best Practices for WASM platform files:

✅ Use timer.cpp for canonical timing functions with EMSCRIPTEN_KEEPALIVE
✅ Use entry_point.cpp for main() and setup/loop coordination with async pumping
✅ Use js.cpp for JavaScript utility functions without duplicating timer functions
✅ Include proper async infrastructure (fl/async.h) in entry points
✅ Comment when removing duplicate implementations to explain unified build conflicts

Testing

The project uses a comprehensive test suite including:

C++ unit tests
Platform compilation tests
Code quality checks (ruff, clang-format)
Example compilation verification

🚨 CRITICAL: Manual compiling of tests should never be attempted. Always put tests in tests/test_<name>.cpp and run with bash test <name>.

The bash test command now automatically detects when test files are added or removed and will clean the build accordingly.

Test Assertion Macros

🚨 CRITICAL: Always use the proper assertion macros for better error messages and debugging:

Equality Assertions:

✅ CORRECT: CHECK_EQ(A, B) - for equality comparisons
❌ INCORRECT: CHECK(A == B) - provides poor error messages

Inequality Assertions:

✅ CORRECT: CHECK_LT(A, B) - for less than comparisons
✅ CORRECT: CHECK_LE(A, B) - for less than or equal comparisons
✅ CORRECT: CHECK_GT(A, B) - for greater than comparisons
✅ CORRECT: CHECK_GE(A, B) - for greater than or equal comparisons
❌ INCORRECT: CHECK(A < B), CHECK(A <= B), CHECK(A > B), CHECK(A >= B)

Boolean Assertions:

✅ CORRECT: CHECK_TRUE(condition) - for true conditions
✅ CORRECT: CHECK_FALSE(condition) - for false conditions
❌ INCORRECT: CHECK(condition) - for boolean checks

String Assertions:

✅ CORRECT: CHECK_STREQ(str1, str2) - for string equality
✅ CORRECT: CHECK_STRNE(str1, str2) - for string inequality
❌ INCORRECT: CHECK(str1 == str2) - for string comparisons

Floating Point Assertions:

✅ CORRECT: CHECK_DOUBLE_EQ(a, b) - for floating point equality
✅ CORRECT: CHECK_DOUBLE_NE(a, b) - for floating point inequality
❌ INCORRECT: CHECK(a == b) - for floating point comparisons

Examples:

// Good assertion usage
CHECK_EQ(expected_value, actual_value);
CHECK_LT(current_index, max_index);
CHECK_GT(temperature, 0.0);
CHECK_TRUE(is_initialized);
CHECK_FALSE(has_error);
CHECK_STREQ("expected", actual_string);
CHECK_DOUBLE_EQ(3.14159, pi_value, 0.001);

// Bad assertion usage
CHECK(expected_value == actual_value);  // Poor error messages
CHECK(current_index < max_index);       // Poor error messages
CHECK(is_initialized);                  // Unclear intent
CHECK("expected" == actual_string);     // Wrong comparison type

Why: Using the proper assertion macros provides:

Better error messages with actual vs expected values
Clearer intent about what is being tested
Consistent debugging across all test failures
Type safety for different comparison types

Test File Creation Guidelines

🚨 CRITICAL: Minimize test file proliferation - Consolidate tests whenever possible

PREFERRED APPROACH:

✅ CONSOLIDATE: Add new test cases to existing related test files
✅ EXTEND: Expand existing TEST_CASE() blocks with additional scenarios
✅ REUSE: Leverage existing test infrastructure and helper functions
✅ COMPREHENSIVE: Create single comprehensive test files that cover entire feature areas

CREATE NEW TEST FILES ONLY WHEN:

✅ Testing completely new subsystems with no existing related tests
✅ Isolated feature areas that don't fit logically into existing test structure
✅ Complex integration tests that require dedicated setup/teardown

AVOID:

❌ Creating new test files for minor bug fixes - add to existing tests
❌ One test case per file - consolidate related functionality
❌ Duplicate test patterns across multiple files
❌ Scattered feature testing - keep related tests together

EXAMPLES:

✅ GOOD - Consolidation:

// Add to existing tests/test_json_comprehensive.cpp
TEST_CASE("JSON - New Feature Addition") {
    // Add new functionality tests to existing comprehensive file
}

❌ BAD - Proliferation:

// Don't create tests/test_json_new_feature.cpp for minor additions
// Instead add to existing comprehensive test file

DEVELOPMENT WORKFLOW:

During Development/Bug Fixing: Temporary test files are acceptable for rapid iteration
Near Completion: MANDATORY - Consolidate temporary tests into existing files
Final Review: Remove temporary test files and ensure comprehensive coverage in main test files

CONSOLIDATION CHECKLIST:

Can this test be added to an existing TEST_CASE in the same file?
Does an existing test file cover the same functional area?
Would this test fit better as a sub-section of a comprehensive test?
Are there duplicate test patterns that can be eliminated?

Why: Maintaining a clean, consolidated test suite:

Easier maintenance - fewer files to manage and update
Better organization - related functionality tested together
Faster builds - fewer compilation units
Cleaner repository - less file clutter
Improved discoverability - easier to find existing test coverage

Test Execution Format

🚨 CRITICAL: Always use the correct test execution format:

✅ CORRECT: bash test <test_name> (e.g., bash test audio_json_parsing)
❌ INCORRECT: ./.build/bin/test_<test_name>.exe
❌ INCORRECT: Running executables directly
❌ INCORRECT: Manual compilation of tests

Examples:

bash test - Run all tests (includes debug symbols)
bash test audio_json_parsing - Run specific test
bash test xypath - Run test_xypath.cpp
bash compile uno --examples Blink - Compile examples

Quick Build Options:

bash test --quick --cpp - Quick C++ tests only (when no *.py changes)
bash test --quick - Quick tests including Python (when *.py changes)

Why: The bash test wrapper handles platform differences, environment setup, and proper test execution across all supported systems.

Use bash test as specified in user rules for running unit tests. For compilation tests, use bash compile <platform> --examples <example> (e.g., bash compile uno --examples Blink).

🚨 FOR BACKGROUND AGENTS: Running bash test is MANDATORY before indicating completion. Use the MCP server validate_completion tool to ensure all tests pass before completing any task.

Debugging and Stack Traces

Stack Trace Setup

The FastLED project supports enhanced debugging through stack trace functionality for crash analysis and debugging.

For Background Agents: Use the MCP server tool setup_stack_traces to automatically install and configure stack trace support:

# Via MCP server (recommended for background agents)
uv run mcp_server.py
# Then use setup_stack_traces tool with method: "auto"

Manual Installation:

Ubuntu/Debian:

sudo apt-get update
sudo apt-get install -y libunwind-dev build-essential

CentOS/RHEL/Fedora:

sudo yum install -y libunwind-devel gcc-c++  # CentOS/RHEL  
sudo dnf install -y libunwind-devel gcc-c++  # Fedora

macOS:

brew install libunwind

Available Stack Trace Methods

LibUnwind (Recommended) - Enhanced stack traces with symbol resolution
Execinfo (Fallback) - Basic stack traces using standard glibc
Windows (On Windows) - Windows-specific debugging APIs
No-op (Last resort) - Minimal crash handling

The build system automatically detects and configures the best available option.

Testing Stack Traces

# Note: Stack trace testing now uses Python build system
# CMake commands are deprecated
cd tests
cmake . && make crash_test_standalone crash_test_execinfo  # DEPRECATED

# Test libunwind version
./.build/bin/crash_test_standalone manual   # Manual stack trace
./.build/bin/crash_test_standalone nullptr  # Crash test

# Test execinfo version  
./.build/bin/crash_test_execinfo manual     # Manual stack trace
./.build/bin/crash_test_execinfo nullptr    # Crash test

Using in Code

#include "tests/crash_handler.h"

int main() {
    setup_crash_handler();  // Enable crash handling
    // Your code here...
    return 0;
}

For Background Agents: Always run the setup_stack_traces MCP tool when setting up a new environment to ensure proper debugging capabilities are available.

Platform Build Information Analysis

The FastLED project includes comprehensive tools for analyzing platform-specific build information, including preprocessor defines, compiler flags, and toolchain paths from build_info.json files generated during compilation.

Overview

Platform build information is stored in .build/{platform}/build_info.json files that are automatically generated when compiling for any platform. These files contain:

Platform Defines - Preprocessor definitions (#define values) specific to each platform
Compiler Information - Paths, flags, and types for C/C++ compilers
Toolchain Aliases - Tool paths for gcc, g++, ar, objcopy, nm, etc.
Build Configuration - Framework, build type, and other settings

Quick Start

1. Generate Build Information

Before analyzing, ensure you have compiled the platform:

# Compile a platform to generate build_info.json
uv run ci/ci-compile.py uno --examples Blink
uv run ci/ci-compile.py esp32dev --examples Blink

This creates .build/{platform}/build_info.json with all platform information.

2. Analyze Platform Defines

Get platform-specific preprocessor defines:

# Command line tool
python3 ci/ci/build_info_analyzer.py --board uno --show-defines

# Via MCP server
uv run mcp_server.py
# Use build_info_analysis tool with: board="uno", show_defines=true

Example output for UNO:

📋 Platform Defines for UNO:
  PLATFORMIO=60118
  ARDUINO_AVR_UNO
  F_CPU=16000000L
  ARDUINO_ARCH_AVR
  ARDUINO=10808
  __AVR_ATmega328P__

Example output for ESP32:

📋 Platform Defines for ESP32DEV:
  ESP32=ESP32
  ESP_PLATFORM
  F_CPU=240000000L
  ARDUINO_ARCH_ESP32
  IDF_VER="v5.3.2-174-g083aad99cf-dirty"
  ARDUINO_ESP32_DEV
  # ... and 23 more defines

3. Compare Platforms

Compare defines between platforms:

# Command line
python3 ci/ci/build_info_analyzer.py --compare uno esp32dev

# Via MCP 
# Use build_info_analysis tool with: board="uno", compare_with="esp32dev"

Shows differences and commonalities between platform defines.

Available Tools

Command Line Tool

Basic Usage:

# List available platforms
python3 ci/ci/build_info_analyzer.py --list-boards

# Show platform defines
python3 ci/ci/build_info_analyzer.py --board uno --show-defines

# Show compiler information
python3 ci/ci/build_info_analyzer.py --board esp32dev --show-compiler

# Show toolchain aliases
python3 ci/ci/build_info_analyzer.py --board teensy31 --show-toolchain

# Show everything
python3 ci/ci/build_info_analyzer.py --board digix --show-all

# Compare platforms
python3 ci/ci/build_info_analyzer.py --compare uno esp32dev

# JSON output for automation
python3 ci/ci/build_info_analyzer.py --board uno --show-defines --json

MCP Server Tool

For Background Agents, use the MCP server build_info_analysis tool:

# Start MCP server
uv run mcp_server.py

# Use build_info_analysis tool with parameters:
# - board: "uno", "esp32dev", "teensy31", etc. or "list" to see available
# - show_defines: true/false (default: true)
# - show_compiler: true/false  
# - show_toolchain: true/false
# - show_all: true/false
# - compare_with: "other_board_name" for comparison
# - output_json: true/false for programmatic use

Supported Platforms

The build info analysis works with ANY platform that generates a build_info.json file:

Embedded Platforms:

✅ UNO (AVR) - 8-bit microcontroller (6 defines)
✅ ESP32DEV - WiFi-enabled 32-bit platform (29 defines)
✅ ESP32S3, ESP32C3, ESP32C6 - All ESP32 variants
✅ TEENSY31, TEENSYLC - ARM Cortex-M platforms
✅ DIGIX, BLUEPILL - ARM Cortex-M3 platforms
✅ STM32, NRF52 - Various ARM platforms
✅ RPIPICO, RPIPICO2 - Raspberry Pi Pico platforms
✅ ATTINY85, ATTINY1616 - Small AVR microcontrollers

Use Cases

For Code Development

Understanding Platform Differences:

# See what defines are available for conditional compilation
python3 ci/ci/build_info_analyzer.py --board esp32dev --show-defines

# Compare two platforms to understand differences
python3 ci/ci/build_info_analyzer.py --compare uno esp32dev

Compiler and Toolchain Information:

# Get compiler paths and flags for debugging builds
python3 ci/ci/build_info_analyzer.py --board teensy31 --show-compiler

# Get toolchain paths for symbol analysis
python3 ci/ci/build_info_analyzer.py --board digix --show-toolchain

For Automation

JSON output for scripts:

# Get defines as JSON for processing
python3 ci/ci/build_info_analyzer.py --board uno --show-defines --json

# Get all build info as JSON
python3 ci/ci/build_info_analyzer.py --board esp32dev --show-all --json

Integration with Other Tools

Build info analysis integrates with other FastLED tools:

Symbol Analysis - Uses build_info.json to find toolchain paths
Compilation - Generated automatically during example compilation
Testing - Provides platform context for test results

Troubleshooting

Common Issues:

"No boards with build_info.json found"
- Solution: Compile a platform first: uv run ci/ci-compile.py {board} --examples Blink
"Board key not found in build_info.json"
- Solution: Check available boards: python3 ci/ci/build_info_analyzer.py --list-boards
"Build info not found for platform"
- Solution: Ensure the platform compiled successfully and check .build/{board}/build_info.json exists

Best Practices

Always compile first before analyzing build information
Use comparison feature to understand platform differences
Check defines when adding platform-specific code
Use JSON output for automated processing and CI/CD
Combine with symbol analysis for complete platform understanding

For Background Agents: Use the MCP server build_info_analysis tool for consistent access to platform build information and proper error handling.

Symbol Analysis for Binary Optimization

The FastLED project includes comprehensive symbol analysis tools to identify optimization opportunities and understand binary size allocation across all supported platforms.

Overview

Symbol analysis examines compiled ELF files to:

Identify large symbols that may be optimization targets
Understand memory allocation across different code sections
Find unused features that can be eliminated to reduce binary size
Compare symbol sizes between different builds or platforms
Provide optimization recommendations based on actual usage patterns

Supported Platforms

The symbol analysis tools work with ANY platform that generates a build_info.json file, including:

Embedded Platforms:

✅ UNO (AVR) - Small 8-bit microcontroller (typically ~3-4KB symbols)
✅ ESP32DEV (Xtensa) - WiFi-enabled 32-bit platform (typically ~200-300KB symbols)
✅ ESP32S3, ESP32C3, ESP32C6, etc. - All ESP32 variants supported

ARM Platforms:

✅ TEENSY31 (ARM Cortex-M4) - High-performance 32-bit (typically ~10-15KB symbols)
✅ TEENSYLC (ARM Cortex-M0+) - Low-power ARM platform (typically ~8-10KB symbols)
✅ DIGIX (ARM Cortex-M3) - Arduino Due compatible (typically ~15-20KB symbols)
✅ STM32 (ARM Cortex-M3) - STMicroelectronics platform (typically ~12-18KB symbols)

And many more! Any platform with toolchain support and build_info.json generation.

Quick Start

1. Prerequisites

Before running symbol analysis, ensure you have compiled the platform:

# Compile platform first (required step)
uv run ci/ci-compile.py uno --examples Blink
uv run ci/ci-compile.py esp32dev --examples Blink
uv run ci/ci-compile.py teensy31 --examples Blink

This generates the required .build/{platform}/build_info.json file and ELF binary.

2. Run Symbol Analysis

Analyze specific platform:

uv run ci/ci/symbol_analysis.py --board uno
uv run ci/ci/symbol_analysis.py --board esp32dev
uv run ci/ci/symbol_analysis.py --board teensy31

Analyze all available platforms at once:

uv run ci/demo_symbol_analysis.py

Using MCP Server (Recommended for Background Agents):

# Use MCP server tools
uv run mcp_server.py
# Then use symbol_analysis tool with board: "uno" or "auto"
# Or use symbol_analysis tool with run_all_platforms: true

Analysis Output

Symbol analysis provides detailed reports including:

Summary Information:

Total symbols count and total size
Symbol type breakdown (text, data, bss, etc.)
Platform-specific details (toolchain, ELF file location)

Largest Symbols List:

Top symbols by size for optimization targeting
Demangled C++ names for easy identification
Size in bytes and percentage of total

Optimization Recommendations:

Feature analysis - unused features that can be disabled
Size impact estimates - potential savings from removing features
Platform-specific suggestions based on symbol patterns

Example Analysis Results

UNO Platform (Small embedded):

================================================================================
UNO SYMBOL ANALYSIS REPORT
================================================================================

SUMMARY:
  Total symbols: 51
  Total symbol size: 3767 bytes (3.7 KB)

LARGEST SYMBOLS (sorted by size):
   1.  1204 bytes - ClocklessController<...>::showPixels(...)
   2.   572 bytes - CFastLED::show(unsigned char)
   3.   460 bytes - main
   4.   204 bytes - CPixelLEDController<...>::show(...)

ESP32 Platform (Feature-rich):

================================================================================
ESP32DEV SYMBOL ANALYSIS REPORT  
================================================================================

SUMMARY:
  Total symbols: 2503
  Total symbol size: 237092 bytes (231.5 KB)

LARGEST SYMBOLS (sorted by size):
   1. 12009 bytes - _vfprintf_r
   2. 11813 bytes - _svfprintf_r
   3.  8010 bytes - _vfiprintf_r
   4.  4192 bytes - port_IntStack

Advanced Features

JSON Output

Save detailed analysis results for programmatic processing:

uv run symbol_analysis.py --board esp32dev --output-json
# Results saved to: .build/esp32dev_symbol_analysis.json

Batch Analysis

Analyze multiple platforms in sequence:

for board in uno esp32dev teensy31; do
    uv run symbol_analysis.py --board $board
done

Integration with Build Systems

The symbol analysis can be integrated into automated build processes:

# In your Python build script
import subprocess
result = subprocess.run(['uv', 'run', 'symbol_analysis.py', '--board', 'uno'], 
                       capture_output=True, text=True)

MCP Server Tools

For Background Agents, use the MCP server tools for symbol analysis:

Generic Symbol Analysis (symbol_analysis tool):
- Works with any platform (UNO, ESP32, Teensy, STM32, etc.)
- Auto-detects available platforms from .build/ directory
- Can analyze single platform or all platforms simultaneously
- Provides comprehensive usage instructions
ESP32-Specific Analysis (esp32_symbol_analysis tool):
- ESP32 platforms only with FastLED-focused filtering
- Includes feature analysis and optimization recommendations
- FastLED-specific symbol identification and grouping

Usage via MCP:

# Start MCP server
uv run mcp_server.py

# Use symbol_analysis tool with parameters:
# - board: "uno", "esp32dev", or "auto"
# - run_all_platforms: true/false
# - output_json: true/false

Troubleshooting

Common Issues:

"build_info.json not found"
- Solution: Compile the platform first: uv run ci/ci-compile.py {board} --examples Blink
"ELF file not found"
- Solution: Ensure compilation completed successfully and check .build/{board}/ directory
"Tool not found" (nm, c++filt, etc.)
- Solution: The platform toolchain isn't installed or configured properly
- Check: Verify PlatformIO platform installation: uv run pio platform list
"No symbols found"
- Solution: The ELF file may be stripped or compilation failed
- Check: Verify ELF file exists and has debug symbols

Debug Mode:

# Run with verbose Python output for debugging
uv run python -v ci/ci/symbol_analysis.py --board uno

Best Practices

Always compile first before running symbol analysis
Use consistent examples (like Blink) for size comparisons
Run analysis on clean builds to avoid cached/incremental build artifacts
Compare results across platforms to understand feature scaling
Focus on the largest symbols first for maximum optimization impact
Use JSON output for automated processing and trend analysis

For Background Agents: Always use the MCP server symbol_analysis tool for consistent results and proper error handling.

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FastLED Project Rules for Cursor

Cursor Configuration

Post-Change Hooks

MCP Server Configuration

FastLED Web Compiler (FOREGROUND AGENTS ONLY)

Project Structure

Key Commands

🤖 AI AGENT LINTING GUIDELINES

FOREGROUND AGENTS (Interactive Development)

BACKGROUND AGENTS (Automated/CI Environments)

Linting Script Integration

When to Use Individual Scripts

Development Guidelines

🚨 CRITICAL: .INO FILE CREATION RULES 🚨

⚠️ THINK BEFORE CREATING .INO FILES ⚠️

🚫 WHEN NOT TO CREATE .INO FILES:

✅ WHEN TO CREATE .INO FILES:

1. Temporary Testing (.ino)

2. Significant New Feature Examples

📋 CREATION CHECKLIST:

🔍 REVIEW CRITERIA:

❌ EXAMPLES OF WHAT NOT TO CREATE:

✅ EXAMPLES OF JUSTIFIED CREATIONS:

🧹 CLEANUP RESPONSIBILITY:

Memory Management with Smart Pointers and Moveable Objects

🔧 CMAKE BUILD SYSTEM ARCHITECTURE (DEPRECATED - NO LONGER USED)

Build System Overview (Historical Reference)

Linker Configuration (Most Important for Build Issues)

Compiler Configuration

Build Options & Configuration

Testing Infrastructure

Build Troubleshooting Guide

🚨 CRITICAL REQUIREMENTS FOR ALL AGENTS (FOREGROUND & BACKGROUND) 🚨

🚨 MANDATORY COMMAND EXECUTION RULES 🚨

FOREGROUND AGENTS (Interactive Development)

Python Code Execution:

Shell Command Execution:

Command Execution Examples:

BACKGROUND AGENTS (Automated/CI Environments)

Python Code Execution:

Shell Command Execution:

Background Agent Command Examples:

DELETE Operations - DANGER ZONE (ALL AGENTS):

Git-Bash Terminal Truncation Issue

Why These Rules Exist:

MANDATORY MEMORY REFRESH BEFORE COMPLETION

🚨 CRITICAL REQUIREMENTS FOR BACKGROUND AGENTS 🚨

MANDATORY PRE-COMPLETION VALIDATION

Background Agent Completion Checklist:

C++ Design Patterns

Code Standards

Avoid std:: Prefixed Functions

Compiler Warning Suppression

Debug Printing

Emoticon and Emoji Usage Policy

Naming Conventions

Container Parameter Types

Exception Handling

JSON Usage - Ideal API Patterns

⚠️ CRITICAL WARNING: C++ ↔ JavaScript Bindings

Key Binding Files (⚠️ HIGH RISK ZONE ⚠️):

Before Making ANY Changes to These Files:

Common Binding Errors:

If You Must Modify Bindings:

🚨 WASM PLATFORM SPECIFIC RULES 🚨

WASM Unified Build Awareness

WASM Async Platform Pump Pattern

WASM Function Signature Matching

WASM Sketch Compilation

WASM Testing Requirements

WASM Platform File Organization

Testing

Test Assertion Macros

Test File Creation Guidelines

Test Execution Format

Debugging and Stack Traces

Stack Trace Setup

Available Stack Trace Methods

Testing Stack Traces

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