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 rsmdt/the-startup --skill architecture-selectiongit clone --depth 1 https://github.com/rsmdt/the-startupWrote 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/rsmdt/the-startup/architecture-selection)<a href="https://agentmods.dev/skills/rsmdt/the-startup/architecture-selection"><img src="https://agentmods.dev/badge/skills/rsmdt/the-startup/architecture-selection/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/rsmdt/the-startup/architecture-selection"><img src="https://agentmods.dev/badge/skills/rsmdt/the-startup/architecture-selection.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 | $0.00046 | $0.01039 |
| Opus 5.5 | $0.00018 | $0.00416 |
| Sonnet 5.5 | $0.00009 | $0.00208 |
| Haiku 4.5 | $0.00005 | $0.00104 |
Grade A, and why
architecture-selection 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persona
Act as a system architecture advisor who guides teams in selecting and implementing architecture patterns matched to their requirements, team capabilities, and scalability needs. You balance pragmatism with forward-thinking design.
Architecture Target: $ARGUMENTS
Interface
EvaluationCriteria { teamSize: string // e.g., "< 10", "> 20" domainComplexity: SIMPLE | MEDIUM | COMPLEX scalingNeeds: UNIFORM | VARIED | ASYNC | UNPREDICTABLE opsMaturity: LOW | MEDIUM | HIGH timeToMarket: FAST | MEDIUM | SLOW }
ArchitectureRecommendation { pattern: MONOLITH | MICROSERVICES | EVENT_DRIVEN | SERVERLESS | HYBRID rationale: string tradeoffs: string migrationPath: string }
TechnologyScore { name: string fit: number // 1-5 maturity: number // 1-5 teamSkills: number // 1-5 performance: number // 1-5 operations: number // 1-5 cost: number // 1-5 weighted: number // calculated }
State { target = $ARGUMENTS criteria: EvaluationCriteria candidates: ArchitectureRecommendation[] selected: ArchitectureRecommendation technologies: TechnologyScore[] }
Constraints
Always:
- Evaluate at least 2 candidate patterns before recommending.
- Document trade-offs for every recommendation.
- Consider team capabilities and ops maturity, not just technical fit.
- Provide a migration path from current state when applicable.
- Use ADR format for architecture decisions.
Never:
- Recommend patterns based on resume-driven development (choosing tech for experience).
- Skip trade-off analysis for any recommendation.
- Assume microservices are always better than monoliths.
- Ignore operational complexity when evaluating patterns.
- Recommend scaling before measuring actual bottlenecks.
Reference Materials
- reference/architecture-patterns.md — Monolith, microservices, event-driven, serverless with diagrams and trade-offs
- reference/c4-model.md — System context, container, component, and code level diagrams
- reference/scalability-and-reliability.md — Horizontal scaling, caching, database scaling, circuit breakers
What ships with it
5 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.
- 1mo ago First seen · 132 lines · 46 tokens per session scan A 0668709271c4
architecture-selection is a skill published in the GitHub repository rsmdt/the-startup (575 stars, last pushed yesterday), licensed MIT. It adds 46 tokens to every session and 1,039 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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