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.
git clone --depth 1 https://github.com/sandraschi/virtualization-mcpWrote 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/rules/sandraschi/virtualization-mcp/architect)<a href="https://agentmods.dev/rules/sandraschi/virtualization-mcp/architect"><img src="https://agentmods.dev/badge/rules/sandraschi/virtualization-mcp/architect/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/rules/sandraschi/virtualization-mcp/architect"><img src="https://agentmods.dev/badge/rules/sandraschi/virtualization-mcp/architect.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 | $0.01196 | $0.01196 |
| Opus 5.5 | $0.00478 | $0.00478 |
| Sonnet 5.5 | $0.00239 | $0.00239 |
| Haiku 4.5 | $0.00120 | $0.00120 |
Grade C, and why
architect scanned grade C with 1 finding 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 1mo 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- **FORBIDDEN**: `&&`, `||`, `mkdir -p`, `rm -rf`, `cp -r`. This is a copy
94% identical to architect — 1 line 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🛠️ System Context & Environment
- Root Directory:
D:/dev/repos - Owner/GitHub:
sandraschi - Hardware: Local RTX 4090 (24GB) + 64GB RAM | OCuLink-optimized.
- Inference: DeepSeek-R1-Vibe (32B Reasoning Distill).
- Integrations: Unity, Blender, Calibre, Plex, and others. See
D:\Dev\repos\mcp-central-docs\integrations\README.md(or mcp-central-docs/integrations/ in workspace).
🧠 Core Partner Mindset (Materialist/Reductionist)
- Zero-Inference Rule: Prioritize technical truth over agreement. Challenge sub-optimal logic.
- Anti-Gaslight: No mocks, no placeholders. All code must be functional.
- Implementation Lifecycle: During early prototype work, temporary placeholders must be explicit. Before release, every placeholder must be either implemented or return explicit
not_implementedplus clear UI Under construction labeling. - No Conversation Fluff: No emojis, apologies, or "rah-rah." Be academic and direct.
- Slop (LDDO) Prevention: High-density code only. Use early returns and guard clauses.
- Disciplined Programming: ZERO uncaught exceptions. Extensive try-except/try-catch blocks. No silent failures.
- Extensive Logging: Use proper
loggermodules. NO nakedprint()orConsole.Log()statements.
🔌 FastMCP 2.14.4 Engineering (Backend)
- Framework: Use FastMCP 2.14.4 and Python 3.13+.
- Pattern: Leverage
@mcp.tool()for side effects and@mcp.resource()for data loading. - Context Usage: Mandatory
ctx: Contextparameter to utilizectx.info()andctx.report_progress(). - Dialogic returns: Tool responses must be conversational (dialogic); support sampling and AI/agentic workflows per FastMCP 2.14+.
- Packaging: Create
.mcpbpackages in thedist/folder. All bundles must be dependency-free, containing extensive prompt templates and validmanifest.jsonexamples. - Deployment: Design for "Local-First" compatibility with the
sandraschiGitHub hub.
🎨 React & Tailwind Standards (Frontend)
- Architecture: Functional components with TypeScript interfaces. Avoid Enums; use Const Objects/Maps.
- Styling: Tailwind CSS ONLY. Use
cn()utility for conditional classes. No inline CSS. - Mobile-First: Responsive by default using
sm:,md:,lg:breakpoints. - Hooks: Logic must be encapsulated in custom hooks; keep UI components "Beautiful and Dumb."
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.
- 1mo ago First seen · 65 lines · 1,196 tokens per session scan C c8c62620c5e4
architect is a cursor rule published in the GitHub repository sandraschi/virtualization-mcp (16 stars, last pushed 2d ago), licensed MIT. It adds 1,196 tokens to every session, about $0.0048 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). It is 94% identical to architect, differing in 1 line, and is treated as a copy.
Other cursor rules, from other repositories
architect
Global Architect rules for sandraschi's dev environment (Unity and other integrations, FastMCP, React). See mcp-central-docs integrations.
architect
Global Architect rules for sandraschi's dev environment (Unity, FastMCP, React).
architect
Global Architect rules for sandraschi's dev environment (Unity, FastMCP, React).
about-codebase
General information about the Lineai MCP Server codebase and its purpose.
runwhen-infrastructure
Infrastructure conventions for scripts targeting Kubernetes and databases via RunWhen runners.
validate-design-early
Ask for design approval before implementing 100+ lines.