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 miiitch/d2-gen --skill d2-gen-azuregit clone --depth 1 https://github.com/miiitch/d2-genWrote 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/miiitch/d2-gen/d2-gen-azure)<a href="https://agentmods.dev/skills/miiitch/d2-gen/d2-gen-azure"><img src="https://agentmods.dev/badge/skills/miiitch/d2-gen/d2-gen-azure/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/miiitch/d2-gen/d2-gen-azure"><img src="https://agentmods.dev/badge/skills/miiitch/d2-gen/d2-gen-azure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00121 | $0.01886 |
| Opus 5 | $0.00060 | $0.00943 |
| Sonnet 5 | $0.00024 | $0.00377 |
| Haiku 4.5 | $0.00012 | $0.00189 |
Grade A, and why
d2-gen-azure 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 10d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
D2 Diagram Generator
When to Use
- Generate architecture diagrams from Terraform or Terragrunt code
- Visualize Azure infrastructure with proper icons, connections, and grouping
- Create
.d2files rendered to SVG/PNG via thed2CLI - Represent resource dependencies, network topology, RBAC, monitoring, and data flows
Goal
Create readable architecture diagrams using D2 language for Azure/Terraform infrastructure.
Output is .d2 text files, rendered to SVG or PNG via the d2 CLI.
Tools
- d2 CLI: Render
.d2files to SVG/PNG:d2 input.d2 output.svg - d2 CLI with layout engine:
d2 --layout=elk input.d2 output.svg - d2 fmt: Format D2 files:
d2 fmt input.d2 - No MCP server is used — the skill generates D2 source code as text.
Icon Source Requirement
Use this Terraform icon mapping as the source of truth:
- Mapping index:
https://raw.githubusercontent.com/miiitch/d2-gen/refs/heads/main/icon-index-terraform-png.json - Base path for icon files:
https://raw.githubusercontent.com/miiitch/d2-gen/refs/heads/main
Resolution rule:
- Look up the Terraform resource type key (e.g.
azurerm_linux_function_app) in the mapping JSON. - The mapped value is a relative path (e.g.
png/Icons/iot/10029-icon-service-Function-Apps.png). - Build the final icon URL: base path +
/+ relative path. - In generated
.d2files, reference the full URL directly inicon:.
Fallback: if no mapping entry exists, use shape: rectangle with a clear text label.
Recommended Workflow
- Read Terraform/Terragrunt files and list all resources + dependencies.
- Analyze sub-resources for each parent and classify as hidden (from registry) or explicit.
- Ask the mandatory Yes/No questionnaire before generating connections or containers (must be asked every time).
- Determine the resource hierarchy before placing nodes.
- Build workload-centric clusters first (workload at center, required resources around it).
- Apply the Hidden Sub-Resources Registry: hide listed sub-resources and represent them as styled connections to the parent resource.
- Resolve icon URLs from the mapping index, then generate the
.d2file with containers, nodes, connections, icons, and styles. - Validate D2 syntax with
d2 fmtbefore sharing. - Render with
d2 --layout=elk input.d2 output.svgand verify output. - If the user wants an autonomous SVG, download mapped icons locally and render a bundled SVG.
- When regenerating an existing diagram, re-resolve icon URLs from the mapping file (and re-download only used icons for autonomous output if needed).
What ships with it
7 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.
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.
- 10d ago First seen · 141 lines · 121 tokens per session scan A 6f1790156b1e
d2-gen-azure is a skill published in the GitHub repository miiitch/d2-gen (19 stars, last pushed 5d ago), licensed MIT. It adds 121 tokens to every session and 1,886 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 2026-08-30.
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