Agent skill

wireless-protocols

Embedded wireless protocol implementation (LoRa, Zigbee, Thread, Matter)

Stars 514
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/embedded-systems/skills/wireless-protocols

SKILL.md

Wireless Protocols Skill

Overview

This skill provides wireless protocol implementation expertise for embedded IoT devices, covering LoRa/LoRaWAN, Zigbee, Thread, and Matter protocols.

Capabilities

LoRa/LoRaWAN

  • LoRaWAN stack configuration
  • Class A/B/C device implementation
  • OTAA and ABP activation
  • ADR (Adaptive Data Rate) configuration
  • Channel plan configuration
  • Downlink handling
  • MAC command processing

Zigbee

  • Coordinator/router/end device setup
  • Zigbee Cluster Library (ZCL)
  • Network formation and joining
  • Binding and reporting configuration
  • OTA upgrade support
  • Green Power device support

Thread

  • OpenThread configuration
  • Network dataset management
  • Commissioner and joiner roles
  • Border router setup
  • SRP (Service Registration Protocol)
  • DNS-SD integration

Matter

  • Matter device implementation
  • Device type configuration
  • Cluster implementation
  • Commissioning flow
  • Multi-admin support
  • OTA provider/requestor

RF Configuration

  • Antenna matching analysis
  • TX power configuration
  • Frequency selection
  • Channel hopping setup
  • Interference mitigation
  • RSSI/LQI monitoring

Certification Preparation

  • RF testing requirements
  • Protocol compliance testing
  • Interoperability testing
  • Documentation preparation

Target Processes

  • device-driver-development.js - Wireless driver implementation
  • low-power-design.js - Low-power wireless optimization
  • functional-safety-certification.js - Wireless certification

Dependencies

  • LoRaWAN stack (LoRaMac-node, LMIC)
  • Zigbee SDK (Silicon Labs, NXP)
  • OpenThread
  • Matter SDK (connectedhomeip)

Usage Context

This skill is invoked when tasks require:

  • LoRaWAN device implementation
  • Zigbee network development
  • Thread/Matter device creation
  • Wireless protocol optimization
  • RF certification preparation

Protocol Comparison

Protocol Range Data Rate Power Mesh
LoRaWAN 15km 0.3-50 kbps Low No
Zigbee 100m 250 kbps Low Yes
Thread 100m 250 kbps Low Yes
Matter 100m Varies Low Via Thread

Configuration Examples

LoRaWAN OTAA

c
static uint8_t DevEui[] = { 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00 };
static uint8_t AppEui[] = { 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00 };
static uint8_t AppKey[] = { 0x00, ..., 0x00 };  // 16 bytes

MibRequestConfirm_t mibReq;
mibReq.Type = MIB_DEV_EUI;
mibReq.Param.DevEui = DevEui;
LoRaMacMibSetRequestConfirm(&mibReq);

Thread Network Configuration

c
otOperationalDataset dataset;
otDatasetCreateNewNetwork(instance, &dataset);
dataset.mChannel = 15;
dataset.mPanId = 0x1234;
otDatasetSetActive(instance, &dataset);

Matter Device Type

cpp
const EmberAfCluster clusters[] = {
    OnOff::Id,
    LevelControl::Id,
    Descriptor::Id,
    Identify::Id
};

Expand your agent's capabilities with these related and highly-rated skills.

a5c-ai/babysitter

gsd-tools

Central utility skill for GSD operations. Provides config parsing, slug generation, timestamps, path operations, and orchestrates calls to other specialized skills. Acts as the unified entry point that the original gsd-tools.cjs provided via its lib/ modules (commands, config, core, init).

514 31
Explore
a5c-ai/babysitter

model-profile-resolution

Resolve model profile (quality/balanced/budget) at orchestration start and map agents to specific models. Enables cost/quality tradeoffs by selecting appropriate AI models for each agent role.

514 31
Explore
a5c-ai/babysitter

verification-suite

Plan structure validation, phase completeness checks, reference integrity verification, and artifact existence confirmation. Provides the structured verification layer ensuring GSD artifacts are well-formed and complete.

514 31
Explore
a5c-ai/babysitter

state-management

STATE.md reading, writing, and field-level updates. Provides cross-session state persistence via .planning/STATE.md with structured fields for current task, completed phases, blockers, decisions, and quick tasks.

514 31
Explore
a5c-ai/babysitter

git-integration

Git commit patterns, formats, and conventions for GSD methodology. Provides atomic commits per task, structured commit messages, planning file commits, branch management, and milestone tag operations.

514 31
Explore
a5c-ai/babysitter

frontmatter-parsing

YAML frontmatter parsing and manipulation for .planning/ documents. Provides read, write, update, query, and validation operations on frontmatter blocks in GSD markdown artifacts.

514 31
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results