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.
git 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/fix-issue)<a href="https://agentmods.dev/commands/vstorm-co/full-stack-ai-agent-template/fix-issue"><img src="https://agentmods.dev/badge/commands/vstorm-co/full-stack-ai-agent-template/fix-issue/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/commands/vstorm-co/full-stack-ai-agent-template/fix-issue"><img src="https://agentmods.dev/badge/commands/vstorm-co/full-stack-ai-agent-template/fix-issue.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00006 | $0.00192 |
| Opus 5.5 | $0.00002 | $0.00077 |
| Sonnet 5.5 | $0.00001 | $0.00038 |
| Haiku 4.5 | $0.00001 | $0.00019 |
Grade A, and why
fix-issue 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.
What it actually says
Fix the issue: $ARGUMENTS
- Understand — search the codebase for relevant code, read the files, understand current behavior
- Reproduce — if possible, identify a test case or request that triggers the issue
- Root cause — trace through Routes → Services → Repositories to find where the bug originates
- Fix — implement the fix following project conventions:
- Domain exceptions in services (not HTTP errors)
db.flush()in repositories (notcommit)- Type hints on all changed signatures
- Test — run
cd backend && uv run pytestto verify no regressions - Lint — run
cd backend && uv run ruff check . --fix && uv run ruff format . - Summary — explain what was changed and why
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 · 17 lines · 6 tokens per session scan A ddb710c18cdf
fix-issue is a command published in the GitHub repository vstorm-co/full-stack-ai-agent-template (1,951 stars, last pushed yesterday), licensed MIT. It adds 6 tokens to every session and 192 once invoked, about $0.0000 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.
Other commands, from other repositories
magic-wand
When /magic-wand [issue description] is invoked, immediately execute the following steps to perform a comprehensive, expert-level analysis and fix when standard debugging approaches have failed.
fix
When /fix is invoked, immediately execute the following steps.
check-cache
Audit caching configuration in $ARGUMENTS for Next.js 15 correctness.
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.