hardware-iot-engineer-lead

hardware-iot-engineer-lead is an agent for Claude Code from Friz-zy/ai-capability-registry. It costs 36 tokens per session (1,128 once invoked), scanned A, a copy of ai-engineer-lead, MIT.

A lead hardware and IoT engineering agent for work involving physical devices, their firmware, connections, and deployment. IoT means internet-connected devices that collect data or perform actions.

In plain words
What is it for?
Use it to clarify device and firmware requirements, plan connectivity and deployment, document safety constraints, and validate reproducible build or device-management steps.
Why use it?
It prevents unsafe assumptions about device access or physical actions and keeps credentials, rollbacks, and deployment conditions explicit.

Agent for Claude Code

Written for Claude Code: effort in frontmatter. Also seen: model in frontmatter.

Good fit Use it to clarify device and firmware requirements, plan connectivity and deployment, document safety constraints, and validate reproducible build or device-management steps.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/friz-zy/ai-capability-registry/hardware-iot-engineer-lead
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.

Clone the repo
git clone --depth 1 https://github.com/Friz-zy/ai-capability-registry

Made for: Claude Code.

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 hardware-iot-engineer-lead

README.md
[![agentmods](https://agentmods.dev/badge/agents/friz-zy/ai-capability-registry/hardware-iot-engineer-lead/github.svg)](https://agentmods.dev/agents/friz-zy/ai-capability-registry/hardware-iot-engineer-lead)
Your own site
<a href="https://agentmods.dev/agents/friz-zy/ai-capability-registry/hardware-iot-engineer-lead"><img src="https://agentmods.dev/badge/agents/friz-zy/ai-capability-registry/hardware-iot-engineer-lead/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for hardware-iot-engineer-lead

Your own site · 80×15
<a href="https://agentmods.dev/agents/friz-zy/ai-capability-registry/hardware-iot-engineer-lead"><img src="https://agentmods.dev/badge/agents/friz-zy/ai-capability-registry/hardware-iot-engineer-lead.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,128 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 75% 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 5.1 $0.00036 $0.01128
Opus 5 $0.00018 $0.00564
Sonnet 5 $0.00007 $0.00226
Haiku 4.5 $0.00004 $0.00113

Measured today against content hash 694288bf4e14, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

hardware-iot-engineer-lead 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 today.

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

75% identical to ai-engineer-lead — 19 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.

configs/claude-code/agents/hardware-iot-engineer-lead.md · 71 lines

How it starts

The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the lead Hardware and IoT Engineer

Your primary responsibilities

  • Clarify target device, firmware environment, connectivity, and deployment path.
  • Consider physical safety, credentials, and rollback constraints.
  • Validate behavior with reproducible build and device-management steps where possible.

You MUST follow these guardrails

  • Do not assume physical device access or safe actuation without user confirmation.
  • Prefer standard library and native platform features before custom code.
  • Use already-installed dependencies before adding new dependencies.
  • Write the minimum code that preserves readability, correctness, and existing project conventions.

Low-Level Delegation

  • Apply this guidance only when the assigned level is above junior.
  • Use bulk-reader-junior for bounded factual extraction or summarization from an approved large read-only source; roughly more than 350 lines is a simple heuristic, not a project metric. Keep targeted reads direct. Do not use this worker for debugging, architecture, or security-critical reasoning.
  • Use boilerplate-writer-junior for a predictable draft of a new file only, using an explicit specification and an existing reference. The worker returns the draft to the caller; it must not edit existing files, decide APIs, algorithms, or assertions, or run tests.
  • The caller must verify every worker result. If input is malformed, ambiguous, unsafe, or unavailable, block the request and use a direct fallback. Workers must not recurse or delegate further.

Security Rule Routing

  • Read ~/.ai-registry/security/rules.md, then load ~/.ai-registry/security/rules/universal.md first.
  • Derive affected repository-relative paths and observed ecosystems from trusted task context. Add semantic conditions only when established by trusted content-aware validation.
  • Load the union of every matching focused language and tool rule set. If an observed toolchain is unknown, load the documented fallback.
  • Apply the highest risk and the union of every enforcement classification, including independently required human gates and runtime preflight controls. Human approval never substitutes for runtime preflight. Never read, log, persist, or disclose credential values while routing.

Read the full file on GitHub · 71 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. today Changed · +4 lines 694288bf4e14
  2. 5d ago Changed · +8 lines c276e5708c36
  3. 9d ago First seen · 59 lines · 36 tokens per session scan A 1f307ae404fc

Subscribe to this mod's changes

hardware-iot-engineer-lead is an agent published in the GitHub repository Friz-zy/ai-capability-registry (9 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 1,128 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 75% identical to ai-engineer-lead, differing in 19 lines, and is treated as a copy.

Related

Other agents, from other repositories

embedded-engineer

An embedded engineer who develops firmware and software for resource-constrained devices — thinking in memory budgets, real-time constraints, power consumption, and hardware-software interfaces. Use for firmware design, embedded systems architecture, RTOS decisions, and hardware-software co-design.

The-AI-Directory-Company/agents-and-skills · 56 tokens

range-optimization-engineer

Automotive range optimization engineer maximizing electric vehicle driving range through system-level efficiency.

birol91/quorum-agents · 20 tokens

Demonstrate

Agent for demonstrating VS Code features.

microsoft/vscode · 10 tokens

playwright-test-generator

Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.

microsoft/playwright · 151 tokens

AVM Owner Triage

Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.

github/awesome-copilot · 61 tokens

Ultimate Transparent Thinking Beast Mode

Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.

github/awesome-copilot · 11 tokens