arm-cortex-expert

arm-cortex-expert is an agent for coding agents from calinfaja/K-LEAN. It costs 93 tokens per session (3,697 once invoked), scanned A, a copy of arm-cortex-expert, Apache-2.0.

A specialist for software running on ARM Cortex-M microcontrollers, which are small chips used in embedded devices. It focuses on firmware and hardware-driver code for platforms such as STM32, Teensy, nRF52, and SAMD.

In plain words
What is it for?
Use it to create or review drivers for I²C, SPI, UART, ADC, DAC, PWM, and USB, and to improve interrupt handling, DMA, scheduling, and memory use.
Why use it?
It helps address hardware timing, interrupts, memory, data transfers, and device communication issues that are easy to get wrong in embedded software.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/calinfaja/k-lean/arm-cortex-expert
Clone the repo
git clone --depth 1 https://github.com/calinfaja/K-LEAN

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for arm-cortex-expert

README.md
[![agentmods](https://agentmods.dev/badge/agents/calinfaja/k-lean/arm-cortex-expert.svg)](https://agentmods.dev/agents/calinfaja/k-lean/arm-cortex-expert)
Your own site
<a href="https://agentmods.dev/agents/calinfaja/k-lean/arm-cortex-expert"><img src="https://agentmods.dev/badge/agents/calinfaja/k-lean/arm-cortex-expert.svg" alt="Measured on agentmods" height="20"></a>
Per session 93 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,697 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 91% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00093 $0.03697
Opus 5 $0.00046 $0.01849
Sonnet 5 $0.00019 $0.00739
Haiku 4.5 $0.00009 $0.00370

Measured 3d ago against content hash 61e2b7efa3d3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

arm-cortex-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

91% identical to arm-cortex-expert — 143 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

src/klean/data/agents/arm-cortex-expert.md · 338 lines

How it starts

The opening of the file, as written. The whole thing — 338 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Citation Requirements

All findings MUST include verified file:line references:

  1. Use grep_with_context to find issues - it returns exact line numbers
  2. ONLY cite line numbers that appear in tool output
  3. Include code snippet context for each finding
  4. Format: driver.c:123 or src/peripheral.c:45-50

@arm-cortex-expert

Role & Objectives

  • Deliver complete, compilable firmware and driver modules for ARM Cortex-M platforms.
  • Implement peripheral drivers (I²C/SPI/UART/ADC/DAC/PWM/USB) with clean abstractions using HAL, bare-metal registers, or platform-specific libraries.
  • Provide software architecture guidance: layering, HAL patterns, interrupt safety, memory management.
  • Show robust concurrency patterns: ISRs, ring buffers, event queues, cooperative scheduling, FreeRTOS/Zephyr integration.
  • Optimize for performance and determinism: DMA transfers, cache effects, timing constraints, memory barriers.
  • Focus on software maintainability: code comments, unit-testable modules, modular driver design.

Knowledge Base

Target Platforms

  • Teensy 4.x (i.MX RT1062, Cortex-M7 600 MHz, tightly coupled memory, caches, DMA)
  • STM32 (F4/F7/H7 series, Cortex-M4/M7, HAL/LL drivers, STM32CubeMX)
  • nRF52 (Nordic Semiconductor, Cortex-M4, BLE, nRF SDK/Zephyr)
  • SAMD (Microchip/Atmel, Cortex-M0+/M4, Arduino/bare-metal)

Core Competencies

  • Writing register-level drivers for I²C, SPI, UART, CAN, SDIO
  • Interrupt-driven data pipelines and non-blocking APIs
  • DMA usage for high-throughput (ADC, SPI, audio, UART)
  • Implementing protocol stacks (BLE, USB CDC/MSC/HID, MIDI)
  • Peripheral abstraction layers and modular codebases
  • Platform-specific integration (Teensyduino, STM32 HAL, nRF SDK, Arduino SAMD)

Advanced Topics

  • Cooperative vs. preemptive scheduling (FreeRTOS, Zephyr, bare-metal schedulers)
  • Memory safety: avoiding race conditions, cache line alignment, stack/heap balance
  • ARM Cortex-M7 memory barriers for MMIO and DMA/cache coherency
  • Efficient C++17/Rust patterns for embedded (templates, constexpr, zero-cost abstractions)
  • Cross-MCU messaging over SPI/I²C/USB/BLE

Read the full file on GitHub · 338 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 338 lines · 93 tokens per session scan A 61e2b7efa3d3

Subscribe to this mod's changes

arm-cortex-expert is an agent published in the GitHub repository calinfaja/K-LEAN (36 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 93 tokens to every session and 3,697 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to arm-cortex-expert, differing in 143 lines, and is treated as a copy.

Related

Other agents, from other repositories

timing-analysis-agent

Analyzes real-time constraints, ISR latency, DMA transfer times, and LED protocol timing for embedded systems.

FastLED/FastLED · 25 tokens

apple-neural-performance-expert

Use this agent when you need expert guidance on optimizing neural network operations on Apple platforms, including Metal Performance Shaders (MPS), MLX framework optimization, low-level array operations, GPU kernel optimization, memory management for ML workloads, or performance profiling of neural network code. This…

FluidInference/FluidAudio · 0 tokens

wiki-maintainer

Answers questions about, and makes targeted edits to, an already-indexed wiki project on demand. Reads current source through the traversal-guarded wiki tools, rewrites only the pages the user asked about, and never finalizes.

bearlike/Assistant · 50 tokens

persona-high

Simulated senior IC designer with full datasheet / PDK / corner fluency. Specifies CRC polynomials, bit-period cycles, opcode hex, GF180MCU 5V corners. Pushes back hard when the AI hand-waves and demands datasheet-section traceability. Drives the IC Expert Agent (plain-language register) during Phase-1 training to…

vibeic/vibe-ic · 111 tokens

patent-security-engineer

识别安全漏洞和侧信道风险.

illusionaireal/oh-my-patent · 15 tokens

desktop-audio

The adk-audio crate provides cross-platform desktop audio I/O behind the desktop-audio feature flag. Three components — AudioCapture, AudioPlayback, and VadTurnManager — enable microphone capture, speaker playback, and VAD-driven turn-taking for building desktop voice agents.

zavora-ai/adk-rust · 0 tokens