Full-Stack AI Agent Template generates full-stack AI applications with a FastAPI backend and Next.js frontend, including agents, retrieval-augmented generation, streaming, authentication, and integrations. It is for building AI products with features such as chat, conversation sharing, administration, and multiple agent or vector-database choices. Catalogue add-ons support the generated applications and their agent workflows.
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 vstorm-co/full-stack-ai-agent-template --skill frontend-featuregit clone --depth 1 https://github.com/vstorm-co/full-stack-ai-agent-templateWrote 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/vstorm-co/full-stack-ai-agent-template/frontend-feature)<a href="https://agentmods.dev/skills/vstorm-co/full-stack-ai-agent-template/frontend-feature"><img src="https://agentmods.dev/badge/skills/vstorm-co/full-stack-ai-agent-template/frontend-feature.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 | $0.00064 | $0.00701 |
| Opus 5 | $0.00032 | $0.00351 |
| Sonnet 5 | $0.00013 | $0.00140 |
| Haiku 4.5 | $0.00006 | $0.00070 |
Grade A, and why
frontend-feature 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.
How it starts
The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Frontend Feature (Next.js 15 + React 19)
The frontend lives in frontend/src/ — App Router, TypeScript, Tailwind, next-intl, and Zustand. Routes are locale-prefixed: app/[locale]/….
Layout
| Path | Purpose |
|---|---|
src/app/[locale]/… |
Pages (route groups: (dashboard), (marketing), (auth)) |
src/app/api/… |
Next.js route handlers that proxy to the backend |
src/lib/ |
API clients (api-client.ts, *-api.ts), query-keys.ts, helpers |
src/components/ |
UI by domain (chat/, kb/, dashboard/, ui/, …) |
src/stores/ |
Zustand stores (one per concern, re-exported from index.ts) |
src/hooks/ |
useChat, useWebSocket, etc. |
Steps
-
Page — add
src/app/[locale]/(dashboard)/<feature>/page.tsx. Default to a Server Component; add"use client"only where you need interactivity. Read params via the async App Router APIs. -
Data access — add a typed client in
src/lib/<feature>-api.tsbuilt onapi-client.ts. Don't scatterfetchcalls in components. For server-side fetching useserver-api.ts. If the backend needs a same-origin proxy (auth cookies), add a handler undersrc/app/api/…. -
Caching keys — register query keys in
src/lib/query-keys.tsso cache invalidation stays consistent. -
Client state — if the feature needs shared client state, add a store in
src/stores/<feature>-store.tsand export it fromstores/index.ts. Keep server data in the data layer; use stores for UI/ephemeral state. -
Components — put reusable pieces in
src/components/<domain>/; compose primitives fromsrc/components/ui/. Keep components under ~100 lines — extract when they grow. -
i18n — user-facing copy goes through
next-intlmessages, not hardcoded strings. Add keys to the message catalog and read them withuseTranslations/getTranslations. -
Verify:
cd frontend bun run type-check && bun run lint bun dev # check the page renders against a running backend (make dev)
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 · 48 lines · 64 tokens per session scan A 367f8954b892
frontend-feature is a skill published in the GitHub repository vstorm-co/full-stack-ai-agent-template (1,879 stars, last pushed 3d ago), licensed MIT. It adds 64 tokens to every session and 701 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
a2ui-renderer
Render A2UI (Agent-to-UI declarative surfaces) in CopilotKit v2. Enable the runtime via CopilotRuntime({ a2ui: {...} }), then enable the provider via . Auto-activates via /info — do NOT manually pass renderActivityMessages. createA2UIMessageRenderer ships from @copilotkit/react-core/v2; low-level primitives…
copilotkit-develop
Use when building AI-powered features with CopilotKit v2 -- adding chat interfaces, registering frontend tools, sharing application context with agents, handling agent interrupts, and working with the CopilotKit runtime.
copilotkit-integrations
Use when wiring an external agent framework (LangGraph, CrewAI, PydanticAI, Mastra, ADK, LlamaIndex, Agno, Strands, Microsoft Agent Framework, or others) into a CopilotKit application via the AG-UI protocol.
copilotkit-upgrade
Use when migrating a CopilotKit v1 application to v2 -- updating package imports, replacing deprecated hooks and components, switching from GraphQL runtime to AG-UI protocol runtime, and resolving breaking API changes.
copilotkit-debug
Use when diagnosing CopilotKit issues -- runtime connectivity failures, agent not responding, streaming errors, tool execution problems, transcription failures, version mismatches, and AG-UI event tracing.
copilotkit-agui
Use when building custom agent backends, implementing the AG-UI protocol, debugging streaming issues, or understanding how agents communicate with frontends. Covers event types, SSE transport, AbstractAgent/HttpAgent patterns, state synchronization, tool calls, and human-in-the-loop flows.