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 skills add pangzhenying2025/hermes-automotive-skills --skill automotive-powertrain-chassisgit clone --depth 1 https://github.com/pangzhenying2025/hermes-automotive-skillsWrote 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/pangzhenying2025/hermes-automotive-skills/automotive-powertrain-chassis)<a href="https://agentmods.dev/skills/pangzhenying2025/hermes-automotive-skills/automotive-powertrain-chassis"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/automotive-powertrain-chassis/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.
<a href="https://agentmods.dev/skills/pangzhenying2025/hermes-automotive-skills/automotive-powertrain-chassis"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/automotive-powertrain-chassis.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00041 | $0.33711 |
| Opus 5 | $0.00020 | $0.16855 |
| Sonnet 5 | $0.00008 | $0.06742 |
| Haiku 4.5 | $0.00004 | $0.03371 |
Grade A, and why
automotive-powertrain-chassis 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.
How it starts
The opening of the file, as written. The whole thing — 3,306 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Automotive Powertrain Chassis
Abs Brake Systems
ABS/EBD Anti-lock Braking System Skill
Overview
Expert skill in Anti-lock Braking System (ABS) and Electronic Brake-force Distribution (EBD) development. Covers wheel slip control, pressure modulation, EBD algorithms, brake-by-wire, regenerative braking coordination, and brake fade compensation.
Core Competencies
1. Wheel Slip Control
- Target Slip Ratio: 10-20% for optimal braking (peak μ on most surfaces)
- Slip Calculation: λ = (vwheel - vvehicle) / vvehicle
- Control Modes: Build-up, Hold, Release phases
- Surface Adaptation: Adjust control aggressiveness for dry/wet/ice
2. Pressure Modulation
- Hydraulic Valve Control: Inlet/outlet solenoids, return pump
- PWM Frequency: 10-20 Hz typical ABS cycling
- Pressure Estimation: No direct sensor, estimate from valve timing
- Pedal Feel: Minimize pulsation feedback to driver
3. Electronic Brake-force Distribution (EBD)
- Dynamic Load Transfer: Front/rear brake bias based on deceleration
- Proportioning: Prevent rear wheel lockup (stability)
- Empty vs Loaded: Adjust distribution based on vehicle weight
- Trailer Detection: Modify EBD for towing conditions
4. Regenerative Braking Coordination
- Blending Control: Seamless transition hydraulic ↔ regenerative
- Regen Priority: Max energy recovery while meeting brake demand
- Pedal Feel: Maintain consistent deceleration feel
- Safety Backup: Full hydraulic if electric system fails
5. Brake-by-Wire (BBW)
- Electro-Mechanical Brakes (EMB): Electric caliper actuators
- Decoupled Pedal: Pedal feel simulator, no direct hydraulic link
- Redundancy: Dual ECUs, backup hydraulic circuit
- Latency: <100ms brake request to force application
Control Algorithms
ABS Slip Control (Bang-Bang with Hysteresis)
typedef enum {
ABS_BUILD, // Increase pressure
ABS_HOLD, // Maintain pressure
ABS_RELEASE // Decrease pressure
} ABS_Phase_t;
typedef struct {
float wheel_speed_mps;
float vehicle_speed_mps;
float slip_ratio;
ABS_Phase_t phase;
uint16_t cycle_count;
} ABS_WheelController_t;
void ABS_WheelControl(ABS_WheelController_t *abs, float dt) {
// Calculate slip ratio
if (abs->vehicle_speed_mps > 0.1f) {
abs->slip_ratio = (abs->vehicle_speed_mps - abs->wheel_speed_mps) / abs->vehicle_speed_mps;
} else {
abs->slip_ratio = 0.0f;
}
// State machine for pressure modulation
switch (abs->phase) {
case ABS_BUILD:
// Normal braking: increase pressure
Hydraulic_OpenInletValve();
Hydraulic_CloseOutletValve();
// Transition to HOLD if slip exceeds threshold
if (abs->slip_ratio > SLIP_THRESHOLD_HIGH) { // 20%
abs->phase = ABS_HOLD;
}
break;
case ABS_HOLD:
// Hold current pressure
Hydraulic_CloseInletValve();
Hydraulic_CloseOutletValve();
// Transition to RELEASE if slip still increasing
if (abs->slip_ratio > SLIP_THRESHOLD_CRITICAL) { // 25%
abs->phase = ABS_RELEASE;
} else if (abs->slip_ratio < SLIP_THRESHOLD_LOW) { // 15%
abs->phase = ABS_BUILD;
}
break;
case ABS_RELEASE:
// Decrease pressure to reduce slip
Hydraulic_CloseInletValve();
Hydraulic_OpenOutletValve();
Hydraulic_ActivateReturnPump();
abs->cycle_count++;
// Transition to BUILD when slip decreases
if (abs->slip_ratio < SLIP_THRESHOLD_LOW) {
abs->phase = ABS_BUILD;
}
break;
}
}
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.
- 12d ago First seen · 3,306 lines · 41 tokens per session scan A 5709968a3b46
automotive-powertrain-chassis is a skill published in the GitHub repository pangzhenying2025/hermes-automotive-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 33,711 once invoked, about $0.0002 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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