can-bus

CAN/CAN-FD bus analysis and development expertise

509 stars

Best use case

can-bus is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

CAN/CAN-FD bus analysis and development expertise

Teams using can-bus should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/can-bus/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/embedded-systems/skills/can-bus/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/can-bus/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How can-bus Compares

Feature / Agentcan-busStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

CAN/CAN-FD bus analysis and development expertise

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# CAN Bus Skill

## Overview

This skill provides comprehensive CAN and CAN-FD bus analysis, development, and debugging capabilities for automotive and industrial embedded systems.

## Capabilities

### Message Frame Operations
- CAN message frame generation
- Frame analysis and decoding
- Identifier filtering and masking
- Standard (11-bit) and extended (29-bit) IDs
- Remote frame handling

### DBC File Support
- DBC file parsing and generation
- Signal decoding and encoding
- Message definition management
- Physical value scaling
- Multiplexed signal support

### Protocol Support
- CAN 2.0A/B compliance
- CAN-FD configuration and validation
- J1939 transport protocol
- CANopen communication
- UDS (ISO 14229) diagnostics
- ISO-TP (ISO 15765-2)

### Bus Analysis
- Bus arbitration analysis
- Error frame detection and analysis
- Bus-off recovery monitoring
- Bus load calculation
- Bit timing verification
- Network topology analysis

### Gateway Operations
- Message routing configuration
- Gateway bridge setup
- Protocol translation
- Filtering and forwarding rules

## Target Processes

- `device-driver-development.js` - CAN driver implementation
- `signal-integrity-testing.js` - CAN bus signal validation
- `hw-sw-interface-specification.js` - CAN interface definition
- `functional-safety-certification.js` - CAN safety requirements

## Dependencies

- CAN interface tools (PEAK, Vector, Kvaser)
- DBC files for signal decoding
- CAN analyzer hardware
- SocketCAN (Linux)

## Usage Context

This skill is invoked when tasks require:
- CAN driver development
- Bus communication debugging
- DBC-based signal analysis
- Protocol stack implementation
- Automotive networking

## Configuration Examples

### CAN Bit Timing
```yaml
can:
  bitrate: 500000  # 500 kbps
  sample_point: 87.5
  sjw: 1
  seg1: 13
  seg2: 2
  prescaler: 4
```

### CAN-FD Configuration
```yaml
can_fd:
  nominal_bitrate: 500000
  data_bitrate: 2000000
  brs: enabled  # Bit Rate Switch
  esi: enabled  # Error State Indicator
```

### DBC Signal Definition
```dbc
BO_ 0x123 EngineData: 8 ECU
 SG_ EngineRPM : 0|16@1+ (0.25,0) [0|16383.75] "rpm" Vector__XXX
 SG_ EngineTemp : 16|8@1+ (1,-40) [-40|215] "C" Vector__XXX
```