automotive-ev-tools

automotive-ev-tools is a skill for Claude Code, Codex from pangzhenying2025/hermes-automotive-skills. It costs 119 tokens per session (7,939 once invoked), scanned A, original, MIT.

A reference skill for designing electric-vehicle battery packs, including cells, modules, cooling, wiring, and safety. It covers automotive standards such as ISO 26262, which addresses functional safety, and AUTOSAR, a software architecture standard for vehicles.

In plain words
What is it for?
Use it for cell selection, battery-pack and module layout, thermal management, battery-management-system integration, safety analysis, and charging-system design.
Why use it?
It brings battery and vehicle-software standards together when planning an EV system.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for cell selection, battery-pack and module layout, thermal management, battery-management-system integration, safety analysis, and charging-system design.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pangzhenying2025/hermes-automotive-skills/automotive-ev-tools
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.

Any agent
npx skills add pangzhenying2025/hermes-automotive-skills --skill automotive-ev-tools
Clone the repo
git clone --depth 1 https://github.com/pangzhenying2025/hermes-automotive-skills

Made for: Claude Code, Codex.

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 automotive-ev-tools

README.md
[![agentmods](https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/automotive-ev-tools/github.svg)](https://agentmods.dev/skills/pangzhenying2025/hermes-automotive-skills/automotive-ev-tools)
Your own site
<a href="https://agentmods.dev/skills/pangzhenying2025/hermes-automotive-skills/automotive-ev-tools"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/automotive-ev-tools/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 automotive-ev-tools

Your own site · 80×15
<a href="https://agentmods.dev/skills/pangzhenying2025/hermes-automotive-skills/automotive-ev-tools"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/automotive-ev-tools.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 119 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,939 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 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 5.1 $0.00119 $0.07939
Opus 5 $0.00060 $0.03970
Sonnet 5 $0.00024 $0.01588
Haiku 4.5 $0.00012 $0.00794

Measured 12d ago against content hash 945e9d14f806, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

automotive-ev-tools 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 12d 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.

skills/automotive-ev-tools/SKILL.md · 779 lines

How it starts

The opening of the file, as written. The whole thing — 779 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Automotive Ev Tools

5 skill files covering ev-tools domain for automotive software engineering.

Applicable Standards

  • ASPICE Level 2/3 for software process
  • ASPICE Level 3
  • AUTOSAR 4.4
  • AUTOSAR 4.4 for software architecture
  • IEC 61851 EV charging systems
  • IEC 63110 Management of EV charging infrastructure
  • IPC-2221 PCB design standards
  • ISO 12405 Lithium-ion battery testing
  • ISO 15118 Vehicle-to-Grid communication
  • ISO 26262
  • ISO 26262 (for automotive variants)
  • ISO 26262 ASIL-C/D for BMS safety functions
  • ISO 6469-1 Electric safety
  • ISO 6469-1 Electric vehicle safety
  • OCPP 1.6J (JSON over WebSocket)
  • OCPP 2.0.1 (ISO 15118 integration)
  • SAE J2464 EV battery abuse testing
  • UL 1973 Batteries for stationary applications
  • UN ECE R100 Battery safety and crash testing
  • UN ECE R100 Battery safety regulations
  • USABC Battery Performance Goals
  • VDA Battery System Standards

Use Cases

  • EV battery pack architecture design
  • Cell selection and benchmarking
  • Module and pack mechanical layout
  • Thermal management system design
  • BMS integration and wiring harness
  • Safety analysis (FMEA, FTA, abuse testing)
  • Weight and cost optimization
  • Modular BMS PCB design and layout
  • bq76940/ISL94202 AFE integration
  • MPPT solar charging integration
  • ThingSet protocol communication
  • Load management and DC/DC control
  • EV charge point software development
  • Central system (CSMS) integration
  • Smart charging and load management
  • OCPP 1.6J and OCPP 2.0.1 protocol implementation
  • Charging session management and billing
  • Open-source BMS software architecture
  • Cell monitoring and balancing algorithms
  • SOC/SOH estimation implementation

Topics Covered

Battery Modeling

  • pybamm-battery-modeling

Bms Hardware

  • libresolar-modular-bms

Bms Software

  • openbms-integration

Charging Infrastructure

  • ocpp-charging-protocol

Pack Design

  • battery-design-studio

Constraints

  • Backward compatibility with OCPP 1.6J for existing infrastructure
  • Billing accuracy requirements (MID-certified meters)
  • Certification costs for automotive production use
  • Component availability for open-source BOM
  • Computational performance for real-time model variants
  • Cost target <$100/kWh at pack level
  • Crash safety compliance (UN ECE R100, FMVSS 305)
  • Firmware memory footprint on STM32L4 (256 KB flash)
  • ISO 26262 ASIL-C/D compliance for safety functions
  • Measurement accuracy requirements (mV for voltage, 0.1A for current)
  • Model complexity vs embedded resource constraints
  • Network reliability (cellular coverage, latency, bandwidth)
  • PCB manufacturing tolerances for high-voltage creepage
  • Package space limitations in vehicle underbody
  • Parameter accuracy from limited cell test data

Read the full file on GitHub · 779 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. 12d ago First seen · 779 lines · 119 tokens per session scan A 945e9d14f806

Subscribe to this mod's changes

automotive-ev-tools is a skill published in the GitHub repository pangzhenying2025/hermes-automotive-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 119 tokens to every session and 7,939 once invoked, about $0.0006 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.

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