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 shawnpang/startup-founder-skills --skill architecture-designgit clone --depth 1 https://github.com/shawnpang/startup-founder-skillsWrote 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/shawnpang/startup-founder-skills/architecture-design)<a href="https://agentmods.dev/skills/shawnpang/startup-founder-skills/architecture-design"><img src="https://agentmods.dev/badge/skills/shawnpang/startup-founder-skills/architecture-design/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/shawnpang/startup-founder-skills/architecture-design"><img src="https://agentmods.dev/badge/skills/shawnpang/startup-founder-skills/architecture-design.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 | $0.00060 | $0.01747 |
| Opus 5.5 | $0.00024 | $0.00699 |
| Sonnet 5.5 | $0.00012 | $0.00349 |
| Haiku 4.5 | $0.00006 | $0.00175 |
Grade A, and why
architecture-design 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- architecture-design — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architecture Design
When to Use
- Starting a new product or major feature that needs system design
- Choosing between monolith, modular monolith, microservices, or event-driven patterns
- Selecting a database (SQL vs NoSQL vs specialized) for a new project
- Analyzing dependencies for circular references, coupling issues, or outdated packages
- Creating architecture diagrams (Mermaid, PlantUML, ASCII) for documentation or review
- Writing Architecture Decision Records (ADRs) for technical choices
- Evaluating scalability bottlenecks or planning capacity
Context Required
From startup-context: product description, tech stack, current state (prototype/beta/scaling), team size, expected scale (users, requests/sec, data volume). If missing, ask:
- What does this system need to do? (core use cases)
- What scale are you targeting? (users, requests/sec, data size)
- What is your team size and backend experience level?
- Are there hard constraints? (compliance, latency, budget, existing infra)
Workflow
- Gather requirements — Identify functional requirements (use cases), non-functional requirements (latency, throughput, availability, consistency), and constraints (budget, team size, compliance).
- Run architecture assessment — Analyze the existing project structure to detect current patterns (MVC, layered, hexagonal, microservices indicators), code organization issues (god classes, mixed concerns), and layer violations.
- Analyze dependencies — Examine the dependency tree for circular dependencies, coupling scores, and outdated packages across npm, Python, Go, or Rust projects.
- Select architecture pattern — Use the decision workflows below to match team size, deployment needs, and data boundaries to the right pattern. For most early-stage startups, recommend modular monolith.
- Select database — Match data characteristics, scale requirements, and consistency needs to the appropriate database technology using the selection workflow below.
- Design data model — Produce an ER diagram in Mermaid. Define entity ownership: which module/service writes, others read via API.
- Define API contracts — Specify key endpoints with method, path, request/response shapes, and error codes. Version from day one.
- Generate architecture diagram — Produce a Mermaid C4 or flowchart diagram showing components, data stores, external services, and communication patterns.
- Write ADRs — Document key decisions using the ADR format below.
- Identify risks — Call out single points of failure, data consistency risks, and scaling bottlenecks with mitigations.
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 · 140 lines · 60 tokens per session scan A edbd79d74140
architecture-design is a skill published in the GitHub repository shawnpang/startup-founder-skills (371 stars, last pushed 7mo ago), licensed MIT. It adds 60 tokens to every session and 1,747 once invoked, about $0.0002 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 2026-08-30.
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