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 usrrname/cursorrules --skill architecturegit clone --depth 1 https://github.com/usrrname/cursorrulesWrote 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/usrrname/cursorrules/architecture)<a href="https://agentmods.dev/skills/usrrname/cursorrules/architecture"><img src="https://agentmods.dev/badge/skills/usrrname/cursorrules/architecture/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/usrrname/cursorrules/architecture"><img src="https://agentmods.dev/badge/skills/usrrname/cursorrules/architecture.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 | $0.00009 | $0.01625 |
| Opus 5.5 | $0.00004 | $0.00650 |
| Sonnet 5.5 | $0.00002 | $0.00325 |
| Haiku 4.5 | $0.00001 | $0.00162 |
Grade A, and why
architecture 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 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.
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 — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architecture Design Command 🏗️
This command guides the AI architect agent to analyze user stories and propose multiple architectural solutions following a structured workflow.
Critical Rules
- Always start with understanding the user's request, the user story, existing constraints, existing architecture, and its business context. Ask clarifying questions to ensure a complete understanding.
- Propose 3 viable solutions. One should be the simplest of the lowest-risk.
- Consider both functional and non-functional requirements
- Offer trade-offs if the user requests them; evaluate trade-offs systematically
- Consider security implications in terms of OWASP Top 10
- Consider impact on existing architecture, if there are any existing
.cursor/.ai/architecture/files - Recommend spikes or proof-of-concepts to validate solutions against system and business constraints
- Evaluate impact on legacy systems (if any) or decisions that are already in place
- Document architectural decisions (ADRs) using
.cursor/rules/templates/architecture-decision-record.md - Architecture document filename conventions:
high-level-architecture.md- shows architecture at system level and the different parts that constitute a solutionsolution_proposal.mdorspike_#.md- should be created as part of a spike task for a problem and stored in.cursor/.ai/spikes/
Workflow Phases
1. Story Analysis
- Clarify business objectives
- Extract functional requirements
- Identify non-functional requirements
- Define constraints and assumptions
- Identify stakeholders
- Map dependencies on legacy systems
- Understand team capabilities and preferences
2. Solution Generation
- Include simple diagrams to illustrate the proposed solutions
- Propose 3 architectural approaches
- Consider different architectural styles
- Evaluate emerging technologies and widely used industry choices based on prior art or best practices by SaaS companies
- Situate the solution in context of the current business and technical constraints and opportunities. (In all likelihood, you are not working at a Big Tech company, and pre-existing SaaS practices will not always be applicable)
- Include up to 5 web-based sources that support the proposed solutions
- Consider build vs. buy options
- Consider open source vs. proprietary solutions
- Assess legacy system integration points
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 · 258 lines · 9 tokens per session scan A 39f540ec0f70
architecture is a skill published in the GitHub repository usrrname/cursorrules (11 stars, last pushed 6mo ago), licensed ISC. It adds 9 tokens to every session and 1,625 once invoked, about $0.0000 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.
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