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-terraformgit 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-terraform)<a href="https://agentmods.dev/skills/pangzhenying2025/hermes-automotive-skills/automotive-terraform"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/automotive-terraform/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-terraform"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/automotive-terraform.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 | $0.00019 | $0.00256 |
| Opus 5 | $0.00010 | $0.00128 |
| Sonnet 5 | $0.00004 | $0.00051 |
| Haiku 4.5 | $0.00002 | $0.00026 |
Grade A, and why
automotive-terraform 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 9d 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.
What it actually says
Automotive Terraform
19 configuration files.
- azure\modules\aks\main.tf
- azure\modules\aks\outputs.tf
- azure\modules\aks\variables.tf
- azure\modules\cosmos-db\main.tf
- azure\modules\iot-hub\main.tf
- azure\modules\iot-hub\outputs.tf
- azure\modules\iot-hub\README.md
- azure\modules\iot-hub\variables.tf
- DECISION_TREE.md
- gcp\modules\iot-core\main.tf
- multi-cloud\crossplane\compositions\vehicle-cluster.yaml
- multi-cloud\crossplane\providers\setup.yaml
- multi-cloud\crossplane\README.md
- multi-cloud\pulumi\hybrid\index.ts
- multi-cloud\pulumi\hybrid\package.json
- multi-region\MULTI_REGION_STRATEGY.md
- MULTI_CLOUD_GUIDE.md
- QUICKSTART.md
- README.md
What ships with it
19 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/azure/modules/aks/main.tf 8.1 KB
- references/azure/modules/aks/outputs.tf 3.4 KB
- references/azure/modules/aks/variables.tf 7.3 KB
- references/azure/modules/cosmos-db/main.tf 8.5 KB
- references/azure/modules/iot-hub/main.tf 8.8 KB
- references/azure/modules/iot-hub/outputs.tf 2.5 KB
- references/azure/modules/iot-hub/README.md 6.5 KB
- references/azure/modules/iot-hub/variables.tf 3.4 KB
- references/DECISION_TREE.md 12 KB
- references/gcp/modules/iot-core/main.tf 11 KB
- references/MULTI_CLOUD_GUIDE.md 12 KB
- references/multi-cloud/crossplane/compositions/vehicle-cluster.yaml 11 KB
- references/multi-cloud/crossplane/providers/setup.yaml 5.3 KB
- references/multi-cloud/crossplane/README.md 15 KB
- references/multi-cloud/pulumi/hybrid/index.ts 15 KB runs code
- references/multi-cloud/pulumi/hybrid/package.json 625 B
- references/multi-region/MULTI_REGION_STRATEGY.md 20 KB
- references/QUICKSTART.md 13 KB
- references/README.md 12 KB
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.
- 9d ago First seen · 31 lines · 19 tokens per session scan A 5ed35247e47c
automotive-terraform is a skill published in the GitHub repository pangzhenying2025/hermes-automotive-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 19 tokens to every session and 256 once invoked, about $0.0001 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 2026-09-03.
Other skills, from other repositories
iso26262
ISO 26262 functional-safety expert that operates in two modes: (1) HARA / ASIL determination — enumerate hazardous events from item malfunctions × driving situations, rate Severity (S0–S3), Exposure (E0–E4), Controllability (C0–C3), look up ASIL from ISO 26262-3:2018 Table 4, and produce a HARA report with Safety…
automotive-syseng
When the user wants to analyze automotive requirements, check INCOSE/EARS compliance, review MISRA-C code, assess ADAS levels, or verify ISO 26262/AUTOSAR/SOTIF conformance. Also use when the user says 'check requirements', 'EARS check', 'INCOSE analysis', 'MISRA check', 'ASIL assessment', 'V-model check'…
automotive-expert
Expert-level automotive systems, connected vehicles, fleet management, telematics, ADAS, and automotive software. Use when the user mentions connected car, fleet, telematics, ADAS, or vehicle, or when the task involves Automotive Systems, Technologies, Standards and Protocols, or Fleet Management.
google-cloud-filestore-autoscale
Inspects Google Cloud Filestore capacity and utilization, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization). Use when monitoring Filestore instance headroom, resizing instance shares, configuring automated growth/shrink thresholds…
terraform-module-library
Build reusable Terraform modules for AWS, Azure, GCP, and OCI infrastructure following infrastructure-as-code best practices. Use when creating infrastructure modules, standardizing cloud provisioning, or implementing reusable IaC components.
vast-gpu
Rent, manage, and destroy GPU instances on vast.ai. Use when user says "rent gpu", "vast.ai", "rent a server", "cloud gpu", or needs on-demand GPU without owning hardware.