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 d-oit/rust-2026-template --skill architecture-diagramgit clone --depth 1 https://github.com/d-oit/rust-2026-templateWrote 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/d-oit/rust-2026-template/architecture-diagram)<a href="https://agentmods.dev/skills/d-oit/rust-2026-template/architecture-diagram"><img src="https://agentmods.dev/badge/skills/d-oit/rust-2026-template/architecture-diagram/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/d-oit/rust-2026-template/architecture-diagram"><img src="https://agentmods.dev/badge/skills/d-oit/rust-2026-template/architecture-diagram.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 | $0.00067 | $0.01194 |
| Opus 5.5 | $0.00027 | $0.00478 |
| Sonnet 5.5 | $0.00013 | $0.00239 |
| Haiku 4.5 | $0.00007 | $0.00119 |
Grade A, and why
architecture-diagram 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 today.
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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview Diagram
Generates a human-friendly overview infographic showing what the project is, how to get started, what's inside, and how it all connects.
Execution
Step 1 — Locate Project Root
ls .agents/ Cargo.toml 2>/dev/null || echo "NOT_FOUND"
Step 2 — Generate the Diagram
python .agents/skills/architecture-diagram/scripts/generate_overview.py \
--root . \
--out .template/overview.excalidraw \
--svg-out .template/overview.svg
The script auto-discovers at runtime:
- Workspace crates →
cargo metadata(with Cargo.toml glob fallback) - AI skills →
.agents/skills/*/directories - Commands →
.opencode/commands/*.md - Quality checks →
config/xtask.jsontier check lists - CI jobs → job IDs across
.github/workflows/*.yml
Step 3 — Sync to Docs
cp .template/overview.svg docs/src/overview.svg
scripts/sync-architecture.sh performs steps 2 and 3 in one shot and is what
the Update Overview Diagram workflow runs.
Step 4 — Confirm and Report
After the script exits:
- Tell the user the output path.
- Report counts: N crates · M skills.
- If counts differ from the last known state, summarize what changed.
Output
.template/overview.excalidraw— editable Excalidraw source.template/overview.svg— generated SVG for docs embedding
What the stats mean
The "BY THE NUMBERS" cards are derived, never hand-written. If a number looks wrong, fix the discovery logic rather than editing the generated files.
| Stat | Source |
|---|---|
| Workspace Members | cargo metadata workspace members (includes examples/* and benchmarks) |
| Crates | directories under crates/ that contain a Cargo.toml |
| AI Skills | .agents/skills/*/SKILL.md |
| CI Jobs | unique job IDs across .github/workflows/*.yml |
| Quality Checks | union of the checks lists for every tier in config/xtask.json |
| Shell scripts | scripts/*.sh |
Quality Checks previously scraped scripts/quality-gates.sh for cargo
invocations. That script is now a thin wrapper around cargo xtask, so the
count collapsed to 1 while the real gate ran nineteen checks. Do not
reintroduce command-scraping for this number.
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.
- today Changed · +40 lines e5ffcbcd7cf3
- 1mo ago Changed · -7 lines d3fb3dca7161
- 1mo ago Changed · +1 lines 83d05ce77d50
- 2mo ago First seen · 96 lines · 67 tokens per session scan A 07ee0b138a48
architecture-diagram is a skill published in the GitHub repository d-oit/rust-2026-template (15 stars, last pushed yesterday), licensed MIT. It adds 67 tokens to every session and 1,194 once invoked, about $0.0003 per session on Opus 5.5. 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.
architecture-diagram compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| architecture-diagramd-oit/rust-2026-template | Skill | 15 | yesterday | MIT | A | 67 | Claude Code, Codex |
| review-backendAndreiBozantan/svelte-axum-template | Skill | 2 | 1mo ago | MIT | A | 54 | Claude Code, Codex |
| yada-yada-yadaAndreiBozantan/svelte-axum-template | Skill | 2 | 1mo ago | MIT | A | 81 | Claude Code, Codex |
| review-frontendAndreiBozantan/svelte-axum-template | Skill | 2 | 1mo ago | MIT | A | 62 | Claude Code, Codex |
| fix-issueAndreiBozantan/svelte-axum-template | Skill | 2 | 1mo ago | MIT | A | 65 | Claude Code, Codex |
| make-it-soAndreiBozantan/svelte-axum-template | Skill | 2 | 1mo ago | MIT | A | 55 | Claude Code, Codex |
| triage-review-findingAndreiBozantan/svelte-axum-template | Skill | 2 | 1mo ago | MIT | A | 59 | Claude Code, Codex |