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 agentmods add commands/vstorm-co/full-stack-ai-agent-template/reviewgit 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/commands/vstorm-co/full-stack-ai-agent-template/review)<a href="https://agentmods.dev/commands/vstorm-co/full-stack-ai-agent-template/review"><img src="https://agentmods.dev/badge/commands/vstorm-co/full-stack-ai-agent-template/review.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 | $0.00006 | $0.00271 |
| Opus 5 | $0.00003 | $0.00135 |
| Sonnet 5 | $0.00001 | $0.00054 |
| Haiku 4.5 | $0.00001 | $0.00027 |
Grade A, and why
review 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 5d 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
Review all staged and unstaged changes in the current branch.
For each changed file, verify:
Architecture:
- Routes only call services, never repositories
- Services raise domain exceptions (NotFoundError, AlreadyExistsError, etc.), not HTTP exceptions
- Repositories use
db.flush()+db.refresh(), neverdb.commit() - DI uses Annotated aliases from
deps.py(CurrentUser, *Svc), not rawDepends()in signatures
Schemas & Types:
- Separate Create/Update/Read/List Pydantic models
- Type hints on all function signatures (params + return)
- Modern syntax:
str | NonenotOptional[str] - Route return type is
-> Any
Code Quality:
- No debug code (print, commented-out code, TODO without issue reference)
- No security issues (SQL injection, exposed secrets, missing auth)
- Consistent naming (snake_case functions, PascalCase classes)
- Imports ordered: stdlib → third-party → local
Validation:
- Run
cd backend && uv run ruff check . - Run
cd backend && uv run pytest(if test files changed)
Provide findings with specific file:line references and suggest fixes.
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.
- 5d ago First seen · 32 lines · 6 tokens per session scan A 31c58a32331a
review is a command published in the GitHub repository vstorm-co/full-stack-ai-agent-template (1,878 stars, last pushed yesterday), licensed MIT. It adds 6 tokens to every session and 271 once invoked, about $0.0000 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 commands, from other repositories
mempalace-init
Set up MemPalace — install the package, initialize a palace, register the MCP server with Cursor, and verify everything works.
impact
Blast radius of a change — impacted callers, tests, and contracts.
status
显示 AIForge 服务端状态.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.