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 agentmods add skills/ea-toolkit/architecture-catalog/dashboardnpx skills add ea-toolkit/architecture-catalog --skill dashboardgit clone --depth 1 https://github.com/ea-toolkit/architecture-catalogWrote 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/ea-toolkit/architecture-catalog/dashboard)<a href="https://agentmods.dev/skills/ea-toolkit/architecture-catalog/dashboard"><img src="https://agentmods.dev/badge/skills/ea-toolkit/architecture-catalog/dashboard.svg" alt="Measured on agentmods" 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 | $0.00020 | $0.00250 |
| Opus 5 | $0.00010 | $0.00125 |
| Sonnet 5 | $0.00004 | $0.00050 |
| Haiku 4.5 | $0.00002 | $0.00025 |
Grade A, and why
dashboard 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 4d 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
Generate Architecture Dashboard
Generate the HTML dashboard and summarize key metrics.
Workflow
- Run:
python scripts/generate_dashboard.py - Confirm dashboard was generated at
dashboard.html - Summarize key metrics from the dashboard
Response Format
**Dashboard Generated:** dashboard.html
**Summary:**
| Domain | Maturity | Elements |
|--------|----------|----------|
| customer-management | X/5 | X |
| ... | ... | ... |
**Layer Distribution:**
| Layer | Count |
|-------|-------|
| Application | X |
| Technology | X |
| Business | X |
| ... | ... |
**Health Indicators:**
- Validation errors: X
- Orphan elements: X
Open dashboard.html in a browser to view the full interactive report.
Notes
- The dashboard provides a visual overview of model health
- Maturity is based on required views per domain (application-landscape, technology-landscape, data-model)
- Suggest opening in browser for full experience
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.
- 4d ago First seen · 48 lines · 20 tokens per session scan A 01ac2d0a1f90
dashboard is a skill published in the GitHub repository ea-toolkit/architecture-catalog (38 stars, last pushed 4mo ago), licensed MIT. It adds 20 tokens to every session and 250 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 2026-08-30.
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