agentmods.dev

chiplab AGENTS.md

A repository guide for Chiplab, a service that runs compiled microcontroller firmware on virtual versions of real boards and captures serial output. It covers setup and examples for several embedded-software frameworks.

In plain words
What is it for?
It helps install and connect Chiplab, choose a board example, upload compiled firmware, run it, and inspect its UART output.
Why use it?
It explains how to connect the service and verify firmware without requiring immediate access to physical hardware.

Instructions file for CodexOpenCode

16 14d ago A scan 1,936 tokens original MIT
View the source file veecle/chiplab
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 instructions/veecle/chiplab/agents-md
Clone the repo
git clone --depth 1 https://github.com/veecle/chiplab

Made for: Codex, OpenCode.

Per session 1,936 This file is loaded in full into every session.
When invoked 1,936 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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 $0.01936 $0.01936
Opus 5 $0.00968 $0.00968
Sonnet 5 $0.00387 $0.00387
Haiku 4.5 $0.00194 $0.00194

Measured 3d ago against content hash c9d0b2035349, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

chiplab AGENTS.md 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.

AGENTS.md · 150 lines

How it starts

The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Machine-readable guide for AI coding agents working in this repository.

What is Chiplab

Chiplab simulates firmware on virtual instances of real microcontrollers: upload a compiled ELF, run it on a named virtual board, read back the captured UART output. (See the README for the human-facing pitch.)

  • MCP endpoint: https://chiplab.veecle.ai/mcp
  • Account / sign-in: https://veecle.ai (self-serve; free tier, no credit card)

This repo ships ready-to-run examples for every supported board, grouped by framework — currently bare-metal (vendor-HAL / direct-register), embassy-rust (the Embassy async runtime), zephyr-os (C on the Zephyr RTOS, built with west), freertos (C on the FreeRTOS kernel, built with make), and threadx (C on the Eclipse ThreadX kernel, built with make), each documented in examples/<framework>/. A user can open this repo, connect their agent to Chiplab, and say "install Chiplab and test it on <board>" — everything an agent needs to do that is below.

1. Install / connect Chiplab

  1. Ensure the user has a veecle.ai account (self-serve sign-up; no manual provisioning).
  2. Add the Chiplab MCP server to the host agent. Per-client configuration is in the README. The endpoint is https://chiplab.veecle.ai/mcp; use chiplab as the server name.
  3. Complete sign-in in the browser when prompted.

2. Verify the connection

Call Chiplab's discovery/help tool with no arguments. A successful response returns an overview of Chiplab. Always call it first in a session — it carries chip-specific gotchas and validated fixes.

3. Pick the example for the board you want

Examples live at examples/<framework>/<board>/. Do not hardcode the board or framework list here — discover it:

  • Call the discovery/help tool for the current set of supported boards and their identifiers (it is authoritative and may be ahead of this repo).
  • For the board↔framework↔example mapping in this repo, read supported-boards.md — the single source of truth (see its Board key column).

Read the full file on GitHub · 150 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 · 150 lines · 1,936 tokens per session scan A c9d0b2035349

Subscribe to this mod's changes

chiplab AGENTS.md is an instructions file published in the GitHub repository veecle/chiplab (16 stars, last pushed 14d ago), licensed MIT. It adds 1,936 tokens to every session, about $0.0097 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 2026-08-30.

Hardware and IoTagentagentic-aihardwaresoftwaresoftware-engineeringvirtualization
Related

Other instructions, from other repositories

copperhead AGENTS.md

Instructions for copperheadhq/copperhead, covering agents.md, repository overview, sources of truth, build and verification and architecture.

copperheadhq/copperhead · 1,073 tokens

copperhead CLAUDE.md

Instructions for copperheadhq/copperhead, covering claude.md, what this repo is, sources of truth, workflow (openspec) and architecture (per spec.md §2).

copperheadhq/copperhead · 1,242 tokens

ii-agent AGENTS.md

Instructions for Intelligent-Internet/ii-agent, covering ii-agent contributor guide, quick start, repository map, mandatory rules and architecture.

Intelligent-Internet/ii-agent · 3,294 tokens

thinkrail AGENTS.md

Instructions for JetBrains/thinkrail, covering thinkrail, module structure & boundaries (top-priority requirement), engine: pi only, in-process, architecture (three rings) and repo layout.

JetBrains/thinkrail · 4,503 tokens

sortie copilot-instructions.md

Instructions for sortie-ai/sortie, covering sortie coding & review standards, 1. layered imports (downward only; violation is critical), 2. concurrency safety, 3. workspace path safety (critical: security boundary) and 4. persistence (sqlite).

sortie-ai/sortie · 1,030 tokens

lime AGENTS.md

AGENTS.md instructions for limecloud/lime, covering lime 源码仓库指南, 事实源, 工程约束, 协议与质量 and 执行方式.

limecloud/lime · 1,517 tokens