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-calibrationgit 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-calibration)<a href="https://agentmods.dev/skills/pangzhenying2025/hermes-automotive-skills/automotive-calibration"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/automotive-calibration/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-calibration"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/automotive-calibration.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 | $0.00055 | $0.14927 |
| Opus 5 | $0.00028 | $0.07463 |
| Sonnet 5 | $0.00011 | $0.02985 |
| Haiku 4.5 | $0.00006 | $0.01493 |
Grade A, and why
automotive-calibration 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.
This is a copy
80% identical to automotive-access-control — 666 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.
How it starts
The opening of the file, as written. The whole thing — 3,134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Automotive Calibration
141 skill files covering calibration domain for automotive software engineering.
Applicable Standards
- ASPICE Level 3
- AUTOSAR 4.4
- ISO 21434
- ISO 26262
Use Cases
- CALIBRATION system development
- Adas Tuning optimization
- Production ECU implementation
- Comfort Tuning optimization
- Doe Methods optimization
- Drivability Tuning optimization
- Emissions Optimization optimization
- Engine Calibration optimization
- Fuel Economy optimization
- Model Based Calibration optimization
- Performance Optimization optimization
- Transmission Calibration optimization
Topics Covered
Adas Tuning
- adas-tuning-001
- adas-tuning-002
- adas-tuning-003
- adas-tuning-004
- adas-tuning-005
- adas-tuning-006
- adas-tuning-007
- adas-tuning-008
- adas-tuning-009
- adas-tuning-010
- adas-tuning-011
- adas-tuning-012
- adas-tuning-013
- adas-tuning-014
Comfort Tuning
- comfort-tuning-001
- comfort-tuning-002
- comfort-tuning-003
- comfort-tuning-004
- comfort-tuning-005
- comfort-tuning-006
- comfort-tuning-007
- comfort-tuning-008
- comfort-tuning-009
- comfort-tuning-010
- comfort-tuning-011
- comfort-tuning-012
- comfort-tuning-013
- comfort-tuning-014
Doe Methods
- doe-methods-001
- doe-methods-002
- doe-methods-003
- doe-methods-004
- doe-methods-005
- doe-methods-006
- doe-methods-007
- doe-methods-008
- doe-methods-009
- doe-methods-010
- doe-methods-011
- doe-methods-012
- doe-methods-013
- doe-methods-014
Drivability Tuning
- drivability-tuning-001
- drivability-tuning-002
- drivability-tuning-003
- drivability-tuning-004
- drivability-tuning-005
- drivability-tuning-006
- drivability-tuning-007
- drivability-tuning-008
- drivability-tuning-009
- drivability-tuning-010
- drivability-tuning-011
- drivability-tuning-012
- drivability-tuning-013
- drivability-tuning-014
Emissions Optimization
- emissions-optimization-001
- emissions-optimization-002
- emissions-optimization-003
- emissions-optimization-004
- emissions-optimization-005
- emissions-optimization-006
- emissions-optimization-007
- emissions-optimization-008
- emissions-optimization-009
- emissions-optimization-010
- emissions-optimization-011
- emissions-optimization-012
- emissions-optimization-013
- emissions-optimization-014
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 · 3,134 lines · 55 tokens per session scan A 95954ffda7ba
automotive-calibration is a skill published in the GitHub repository pangzhenying2025/hermes-automotive-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 55 tokens to every session and 14,927 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 80% identical to automotive-access-control, differing in 666 lines, and is treated as a copy.
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