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.
npx agentmods add skills/lhbsaa/embedded-dev-skill/embedded-brainstormingnpx skills add lhbsaa/embedded-dev-skill --skill embedded-brainstorminggit clone --depth 1 https://github.com/lhbsaa/embedded-dev-skillWrote 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.
[](https://agentmods.dev/skills/lhbsaa/embedded-dev-skill/embedded-brainstorming)<a href="https://agentmods.dev/skills/lhbsaa/embedded-dev-skill/embedded-brainstorming"><img src="https://agentmods.dev/badge/skills/lhbsaa/embedded-dev-skill/embedded-brainstorming.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00025 | $0.00861 |
| Opus 5 | $0.00013 | $0.00430 |
| Sonnet 5 | $0.00005 | $0.00172 |
| Haiku 4.5 | $0.00003 | $0.00086 |
Grade A, and why
embedded-brainstorming 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Embedded Brainstorming
Overview
Turn hardware ideas into fully formed designs through systematic exploration.
Core principle: No code generation until hardware configuration confirmed and design approved.
Process Flow
1. Load Context → 2. Confirm Hardware → 3. Identify Constraints → 4. Propose Design → 5. Get Approval → 6. Next Skill
Checklist
You MUST complete these items in order:
1. Load Context
read AGENTS.md
- If AGENTS.md missing → Create template with project info
- Store key config in session
2. Confirm Hardware
Ask questions one at a time:
| Question | Why |
|---|---|
| Target chip? | Determines framework and constraints |
| Interface type? | SPI/I2C/UART config differs |
| Controller/model? | Datasheet lookup required |
| Resolution/config? | Display/sensor specific |
Prefer multiple choice when possible:
"Which chip family?"
A) ESP32-S3 (Wi-Fi, LCD, AI)
B) STM32F4 (Performance, DSP)
C) RP2040 (Low cost, PIO)
D) nRF52 (BLE, Low power)
3. Identify Constraints
Check hard limits:
| Chip | Key Constraint |
|---|---|
| ESP32-S3 | SPI DMA <= 4092 bytes |
| STM32 | Check DMA stream limits |
| RP2040 | PIO instruction limit |
| nRF52 | SoftDevice memory |
4. Propose 2-3 Approaches
Present options with trade-offs:
Approach A: [Recommended]
- Pros: ...
- Cons: ...
- Why recommended: ...
Approach B: [Alternative]
- Pros: ...
- Cons: ...
Approach C: [Fallback]
- Pros: ...
- Cons: ...
5. Get Approval
Present design in sections (scaled to complexity):
## Hardware Configuration
- Chip: ESP32-S3
- Interface: SPI Mode 0, 40MHz
- Controller: ST7789
- Resolution: 240x240
## Architecture
- Three-layer: App → HAL → Driver
## Key Constraints
- DMA: 4092 byte chunks
- Frame buffer: Use PSRAM
## Implementation Plan
- Phase 1: Driver init
- Phase 2: Display functions
- Phase 3: GUI integration
Does this look correct?
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.
- 4d ago First seen · 155 lines · 25 tokens per session scan A 19f4baa7d2f7
embedded-brainstorming is a skill published in the GitHub repository lhbsaa/embedded-dev-skill (9 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 861 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
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embedded-debug
Firmware crash analysis, stack trace decoder, and register dump interpreter for ESP32/ARM/AVR platforms. Use when debugging device crashes, panics, guru meditation errors, hard faults, or analyzing core dumps.
platform-port
Guide porting FastLED to new MCU platforms, including int.h types, clockless drivers, SPI implementations, and platform detection. Use when adding support for a new microcontroller family or board.
memory-audit
Audit embedded code for stack overflow risks, heap fragmentation, static allocation patterns, and memory leaks. Use when investigating OOM crashes, optimizing memory usage, or reviewing memory-critical code on constrained devices.