Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/realmpastai-web/claude-design-suitenpx agentmods add skills/realmpastai-web/claude-design-suite/pick-tech-stackWrote 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/realmpastai-web/claude-design-suite/pick-tech-stack)<a href="https://agentmods.dev/skills/realmpastai-web/claude-design-suite/pick-tech-stack"><img src="https://agentmods.dev/badge/skills/realmpastai-web/claude-design-suite/pick-tech-stack.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 5.1 | $0.00077 | $0.00533 |
| Opus 5 | $0.00039 | $0.00267 |
| Sonnet 5 | $0.00015 | $0.00107 |
| Haiku 4.5 | $0.00008 | $0.00053 |
Grade A, and why
pick-tech-stack 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 7d 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
Pick Tech Stack
Context
You are a staff engineer advising a team on their frontend stack for $ARGUMENTS. data/stacks/*.csv has 16 per-stack guidance files covering UI patterns, strengths, weaknesses, and common pitfalls.
Domain Context
- Stack choice is a 3-axis tradeoff: time-to-first-pixel, long-term maintainability, and hire-ability.
- Next.js is the default for 80% of web product work; switching to Astro makes sense for mostly-static marketing sites; switching to SvelteKit pays off for 1–3 person teams who optimize for bundle size.
- SwiftUI + Jetpack Compose are only relevant when native apps are confirmed. React Native sits between.
- shadcn/ui is not a stack — it's a pattern on top of React/Next. Recommend it as a companion to Next.js.
Instructions
- Ask: team size, deployment target (web / native / both), performance budget (TTI target), design-system intent (greenfield or existing).
- Run:
then for each candidate stack:python scripts/search.py "<deployment> <team-size> <performance>" --max-results 3python scripts/search.py "design system" --stack <stack-name> - For the top recommendation, emit:
- Stack name + 1-line why
- 3-point tradeoff (pros / cons / break-even size)
- Recommended companion libraries (e.g., Next.js + shadcn + Tailwind + TanStack Query)
- A "do not use this if…" disclaimer
- Propose a secondary stack for comparison and explain when to prefer it.
- If SSR/ISR is critical, bias toward Next.js or Astro. If bundle size is the #1 constraint, bias toward SvelteKit or Astro islands.
Further Reading
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.
- 7d ago First seen · 43 lines · 77 tokens per session scan A 659f16d34b6d
pick-tech-stack is a skill published in the GitHub repository realmpastai-web/claude-design-suite (2 stars, last pushed 4mo ago), licensed MIT. It adds 77 tokens to every session and 533 once invoked, about $0.0004 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 2026-08-31.
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