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Freertos

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mohitmishra786
freertos

FreeRTOS skill for embedded RTOS development. Use when creating tasks, managing priorities, using queues and mutexes, detecting stack overflows, configuring FreeRTOS via FreeRTOSConfig.h, or debugging FreeRTOS applications with OpenOCD and GDB. Activates on queries about FreeRTOS tasks, queues, semaphores, mutexes, configASSERT, stack overflow, vTaskDelay, or FreeRTOS-aware debugging.

Overview

Publishermohitmishra786
Repositorylow-level-dev-skills
Skill namefreertos
Stars
266
Forks
31
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mohitmishra786 on GitHub. Read the source before you install it.

Installation

Install the Freertos AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/mohitmishra786/low-level-dev-skills/tree/main/skills/embedded/freertos
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mohitmishra786/low-level-dev-skills.git /tmp/low-level-dev-skills
mkdir -p .claude/skills
cp -r /tmp/low-level-dev-skills/skills/embedded/freertos .claude/skills/freertos
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Freertos in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Freertos on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Freertos is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

FreeRTOS

Purpose

Guide agents through FreeRTOS application development: task creation and priorities, inter-task communication with queues and semaphores, stack overflow detection, configASSERT, and FreeRTOS-aware debugging with GDB and OpenOCD.

Triggers

  • "How do I create a FreeRTOS task?"
  • "How do I pass data between FreeRTOS tasks?"
  • "My FreeRTOS task is crashing — how do I detect stack overflow?"
  • "How do I use FreeRTOS mutexes?"
  • "How do I debug FreeRTOS tasks with GDB?"
  • "How do I configure FreeRTOSConfig.h?"

Workflow

1. Task creation and priorities

c
#include "FreeRTOS.h"
#include "task.h"

// Task function signature
void vMyTask(void *pvParameters) {
    const char *name = (const char *)pvParameters;
    for (;;) {
        // Task body — must never return
        printf("Task %s running\n", name);
        vTaskDelay(pdMS_TO_TICKS(500));  // yield for 500ms
    }
}

int main(void) {
    // xTaskCreate(function, name, stack_depth_words, param, priority, handle)
    TaskHandle_t xHandle = NULL;
    xTaskCreate(vMyTask, "MyTask",
                configMINIMAL_STACK_SIZE + 128,  // words, not bytes!
                (void *)"sensor",
                tskIDLE_PRIORITY + 2,            // higher = more urgent
                &xHandle);

    vTaskStartScheduler();  // never returns if heap is sufficient
    for (;;);               // should never reach here
}

Priority guidelines:

  • tskIDLE_PRIORITY (0) — idle task, never block here
  • ISR-deferred tasks — highest priority to service interrupts quickly
  • Avoid priorities above configMAX_PRIORITIES - 1

2. Queues — inter-task data passing

c
#include "queue.h"

typedef struct { uint32_t sensor_id; float value; } SensorReading_t;

QueueHandle_t xSensorQueue;

void vProducerTask(void *pvParam) {
    SensorReading_t reading;
    for (;;) {
        reading.sensor_id = 1;
        reading.value = read_adc();
        // Send; block max 10ms if queue full
        xQueueSend(xSensorQueue, &reading, pdMS_TO_TICKS(10));
        vTaskDelay(pdMS_TO_TICKS(100));
    }
}

void vConsumerTask(void *pvParam) {
    SensorReading_t reading;
    for (;;) {
        // Block forever until item available
        if (xQueueReceive(xSensorQueue, &reading, portMAX_DELAY) == pdTRUE) {
            process(reading.value);
        }
    }
}

// Create before starting scheduler
xSensorQueue = xQueueCreate(10, sizeof(SensorReading_t));

From ISR: use xQueueSendFromISR() and pass &xHigherPriorityTaskWoken.

3. Semaphores and mutexes

c
#include "semphr.h"

// Binary semaphore — signaling (ISR→task)
SemaphoreHandle_t xSem = xSemaphoreCreateBinary();

void UART_ISR(void) {
    BaseType_t xWoken = pdFALSE;
    xSemaphoreGiveFromISR(xSem, &xWoken);
    portYIELD_FROM_ISR(xWoken);
}

void vUartTask(void *p) {
    for (;;) {
        xSemaphoreTake(xSem, portMAX_DELAY);
        // process received data
    }
}

// Mutex — mutual exclusion (NOT from ISR)
SemaphoreHandle_t xMutex = xSemaphoreCreateMutex();

void vCriticalSection(void) {
    if (xSemaphoreTake(xMutex, pdMS_TO_TICKS(100)) == pdTRUE) {
        // protected access
        shared_resource++;
        xSemaphoreGive(xMutex);
    }
}

// Recursive mutex (same task can take multiple times)
SemaphoreHandle_t xRecursive = xSemaphoreCreateRecursiveMutex();
xSemaphoreTakeRecursive(xRecursive, portMAX_DELAY);
xSemaphoreGiveRecursive(xRecursive);

Use mutex (not binary semaphore) for shared resources to get priority inheritance.

4. Stack overflow detection

c
// FreeRTOSConfig.h
#define configCHECK_FOR_STACK_OVERFLOW  2  // Method 2 (pattern + watermark)
#define configUSE_MALLOC_FAILED_HOOK    1

// Implement the hook (called when overflow detected)
void vApplicationStackOverflowHook(TaskHandle_t xTask, char *pcTaskName) {
    // Log the offending task name, then halt
    configASSERT(0);  // triggers assertion failure
}

void vApplicationMallocFailedHook(void) {
    configASSERT(0);
}

Check watermarks at runtime:

c
// Returns minimum ever free stack words
UBaseType_t uxHighWaterMark = uxTaskGetStackHighWaterMark(xHandle);
printf("Stack headroom: %lu words\n", uxHighWaterMark);
// Rule of thumb: keep headroom > 20 words

5. Essential FreeRTOSConfig.h settings

c
// FreeRTOSConfig.h — adapt to your MCU
#define configCPU_CLOCK_HZ              (SystemCoreClock)
#define configTICK_RATE_HZ              1000          // 1ms tick
#define configMAX_PRIORITIES            8
#define configMINIMAL_STACK_SIZE        128           // words
#define configTOTAL_HEAP_SIZE           (16 * 1024)  // bytes
#define configMAX_TASK_NAME_LEN         16

// Debug / safety
#define configUSE_TRACE_FACILITY        1
#define configUSE_STATS_FORMATTING_FUNCTIONS  1
#define configCHECK_FOR_STACK_OVERFLOW  2
#define configUSE_MALLOC_FAILED_HOOK    1
#define configASSERT(x) if((x)==0) { taskDISABLE_INTERRUPTS(); for(;;); }

// Features
#define configUSE_MUTEXES               1
#define configUSE_RECURSIVE_MUTEXES     1
#define configUSE_COUNTING_SEMAPHORES   1
#define configUSE_TIMERS                1
#define configTIMER_TASK_STACK_DEPTH    (configMINIMAL_STACK_SIZE * 2)

6. GDB debugging with OpenOCD

bash
# Connect GDB with FreeRTOS thread awareness
# OpenOCD provides FreeRTOS-aware RTOS plugin

# openocd.cfg addition
# source [find rtos/FreeRTOS.cfg]  # auto-loads with most targets

# GDB session
(gdb) info threads          # lists all FreeRTOS tasks
(gdb) thread 3              # switch to task 3
(gdb) bt                    # backtrace of that task's stack
(gdb) frame 2               # inspect specific frame

# Print task list from GDB (if trace facility enabled)
(gdb) call vTaskList(buf)
(gdb) printf "%s\n", buf

7. FreeRTOS v11 API updates

FreeRTOS v11 (2024+) extends task notifications and stream buffers:

c
// Task notifications v2 — 32-bit values with action semantics
xTaskNotifyIndexed(xHandle, 0, ulValue, eSetValueWithOverwrite);
xTaskNotifyWaitIndexed(0, 0, ULONG_MAX, &ulNotified, portMAX_DELAY);

// Stream buffers — ISR-safe send with trigger level
xStreamBufferSend(xStream, data, len, 0);
xStreamBufferSetTriggerLevel(xStream, 1);  // wake receiver on 1 byte

Check FreeRTOS.h tskKERNEL_VERSION_NUMBER at compile time for API availability.

8. ARM TrustZone integration

Secure/non-secure world split on Cortex-M33/M55:

c
#include "secure_context.h"

// Initialize secure context management (secure side or NSC veneer)
SecureContext_Init();

// Allocate secure context for task calling secure functions
xTaskCreateSecure(vSecureTask, "SecTask", STACK, NULL, priority, &xHandle);

// MPU defines NSC (Non-Secure Callable) regions for SG veneers

Requires TrustZone-enabled MCU, secure firmware partition, and NSC linker section placement.

9. FreeRTOS+TCP basics

c
#include "FreeRTOS_IP.h"
#include "FreeRTOS_Sockets.h"

// After network stack init (FreeRTOS_IPInit)
Socket_t xSocket = FreeRTOS_socket(FREERTOS_AF_INET, FREERTOS_SOCK_STREAM,
                                   FREERTOS_IPPROTO_TCP);
FreeRTOS_connect(xSocket, &xAddress, sizeof(xAddress));
FreeRTOS_send(xSocket, buffer, len, 0);

Configure buffer counts and TCP/IP options in FreeRTOSIPConfig.h (e.g., ipconfigUSE_TCP, ipconfigNUM_NETWORK_BUFFER_DESCRIPTORS). Pairs with an Ethernet MAC driver and FreeRTOS+TCP buffer management.

10. MPU region configuration

c
// Restricted task with MPU regions (Cortex-M with MPU)
static const TaskParameters_t xRestrictedTaskParams = {
    .pvTaskCode = vRestrictedTask,
    .pcName = "Restricted",
    .usStackDepth = configMINIMAL_STACK_SIZE,
    .pvParameters = NULL,
    .uxPriority = tskIDLE_PRIORITY + 1,
    .puxStackBuffer = stackBuffer,
    .xRegions = {
        { .pvBaseAddress = 0x20000000, .ulLength = 0x10000,
          .ulParameters = tskMPU_REGION_READ_ONLY | tskMPU_REGION_EXECUTE_NEVER },
        { .pvBaseAddress = 0x00000000, .ulLength = 0, .ulParameters = 0 }  // terminator
    }
};
xTaskCreateRestricted(&xRestrictedTaskParams, &xHandle);

Define separate RAM regions for read-only code/data, privileged peripherals, and task-private stacks.

For OpenOCD setup details, see skills/embedded/openocd-jtag. For FreeRTOSConfig.h reference, see references/freertos-config.md.

Related skills

  • Use skills/embedded/openocd-jtag for GDB/OpenOCD remote debugging setup
  • Use skills/embedded/linker-scripts for placing FreeRTOS heap in specific RAM regions
  • Use skills/debuggers/gdb for general GDB session management
  • Use skills/embedded/zephyr for an alternative RTOS with built-in device management

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Freertos AI skill do?

FreeRTOS skill for embedded RTOS development. Use when creating tasks, managing priorities, using queues and mutexes, detecting stack overflows, configuring FreeRTOS via FreeRTOSConfig.h, or debugging FreeRTOS applications with OpenOCD and GDB. Activates on queries about FreeRTOS tasks, queues, semaphores, mutexes, configASSERT, stack overflow, vTaskDelay, or FreeRTOS-aware debugging.

Why use Freertos on TypingMind?

Because you install it once and use it with any model. Freertos is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Freertos in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mohitmishra786/low-level-dev-skills/tree/main/skills/embedded/freertos. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Freertos?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Freertos?

As many as you like. As long as a model supports skills, you can use Freertos with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Freertos AI skill free?

Yes. It is published on GitHub by mohitmishra786 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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