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 agentmods add skills/vpeetla-ai/react-agent-pattern/deploy-vercel-rendernpx skills add vpeetla-ai/react-agent-pattern --skill deploy-vercel-rendergit clone --depth 1 https://github.com/vpeetla-ai/react-agent-patternWhat 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 | $0.00055 | $0.00381 |
| Opus 5 | $0.00028 | $0.00191 |
| Sonnet 5 | $0.00011 | $0.00076 |
| Haiku 4.5 | $0.00006 | $0.00038 |
Grade A, and why
deploy-vercel-render scanned grade A 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 2d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl https://loopforge-api.onrender.com/health This is a copy
100% identical to deploy-vercel-render — 0 lines 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.
What it actually says
Deploy: Vercel + Render
Standard split
| Layer | Host | Config |
|---|---|---|
| UI demo | Vercel | vercel.json, config.js API URL |
| Python API | Render | render.yaml, Dockerfile |
Render free tier
# render.yaml
plan: free # REQUIRED — avoids credit card prompt
Env vars (Render)
GROQ_API_KEY,GITHUB_TOKEN(LoopForge)AEGISAI_API_BASE_URL(gateway integrations)- Never commit secrets — Render dashboard only
Vercel
- Deploy from subfolder:
cd demo && vercel --prod - Point
LOOPFORGE_API/API_BASEinconfig.jsto Render URL
Health checks
curl https://loopforge-api.onrender.com/health
Cold start
- Render free spins down ~15min idle — document in README
- Vercel edge is always warm for static
Reference deploys
| Project | Demo | API |
|---|---|---|
| LoopForge | demo-omega-taupe.vercel.app | loopforge-api.onrender.com |
| Enterprise RAG | enterprise-rag-platform.vercel.app | — |
| VAP | venkat-ai-platform.vercel.app | — |
Docs
Each repo: docs/DEPLOY.md with exact commands and env table
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.
- 2d ago First seen · 58 lines · 55 tokens per session scan A 2c0ffe439415
deploy-vercel-render is a skill published in the GitHub repository vpeetla-ai/react-agent-pattern (2 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 381 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to deploy-vercel-render, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
lesson-quiz
Test a learner on a single Claude Code tutorial lesson (01-10) with 10 questions, scoring answers and flagging weak spots. Use before, during, or after a lesson. Don't use for whole-tutorial assessment or explaining a topic instead of testing it.
self-assessment
Comprehensive Claude Code self-assessment and learning path advisor. Runs a multi-category quiz covering 10 feature areas, produces a detailed skill profile with per-topic scores, identifies specific gaps, and generates a personalized learning path with prioritized next steps. Use when asked to "assess my level"…
backend-interview
模拟后端技术面试，基于简历生成针对性问题.
technology-learning-judgment
Use when creating, revising, or reviewing technical learning material, a technical proposal, or AI-generated implementation that needs accurate mechanism explanations, honest capability boundaries, and industry alternatives rather than API summaries or inflated claims.
aegis-gateway
Integrate AegisAI gateway before tool side effects (notify, publish, deploy). Use when adding Slack/Telegram/WhatsApp notify, content publish, or any irreversible external action in VAP, AegisLoop, or ai-content-factory.
deploy-vercel-render
Deploy vpeetla-ai demos: Vercel static/Next.js frontends, Render FastAPI backends, env vars, free tier gotchas. Use when shipping demos, fixing deploy failures, or adding render.yaml / vercel.json.