REPOGEO REPORT · LITE

a16z-infra/ai-getting-started

Default branch main · commit b02e524a · scanned 6/22/2026, 6:58:02 PM

GitHub: 4,138 stars · 664 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

28 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

2 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface a16z-infra/ai-getting-started, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

hightopics#1

Add relevant topics to the repository

Why:

COPY-PASTE FIX

javascript, nextjs, ai, generative-ai, llm, vector-database, full-stack, starter-kit, template, web-application, clerk, pinecone, replicate, openai, langchain

highreadme#2
Reposition the README H1 to specify the repository's category
Why:
CURRENT
```
# AI Getting Started
```
COPY-PASTE FIX
```
# AI Getting Started: A Full-Stack JavaScript Template for Generative AI Web Apps
```

mediumreadme#3

Add a concise introductory paragraph to the README

Why:

COPY-PASTE FIX

This repository provides a comprehensive, opinionated full-stack JavaScript template designed to jumpstart your generative AI web application projects. It integrates popular tools like Next.js, Langchain.js, OpenAI, Replicate, and Pinecone, offering a complete setup for building AI-powered experiences for developers and technical founders.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface a16z-infra/ai-getting-started

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Next.js

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Next.js · recommended 1×
Vercel AI SDK · recommended 1×
LangChain.js · recommended 1×
LlamaIndex.js · recommended 1×
create-t3-app · recommended 1×

CATEGORY QUERY
What's a good full-stack JavaScript starter kit for building generative AI web applications?
you: not recommended
AI recommended (in order):
1. Next.js
2. Vercel AI SDK
3. LangChain.js
4. LlamaIndex.js
5. create-t3-app
6. TypeScript
7. tRPC
8. Tailwind CSS
9. Prisma
10. Remix
11. Astro
12. Node.js
13. Express.js
14. Fastify
15. NestJS
16. Nuxt.js
AI recommended 16 alternatives but never named a16z-infra/ai-getting-started. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking a modern web development stack for AI projects, integrating large language models and vector databases.
you: not recommended
AI recommended (in order):
1. Next.js (vercel/next.js)
2. Vercel
3. Python
4. FastAPI (tiangolo/fastapi)
5. Django (django/django)
6. PostgreSQL
7. pgvector (pgvector/pgvector)
8. Pinecone
9. Weaviate (weaviate/weaviate)
10. SvelteKit (sveltejs/kit)
11. Qdrant (qdrant/qdrant)
12. Milvus (milvus-io/milvus)
13. Nuxt.js (nuxt/nuxt)
14. Chroma (chromadb/chroma)
15. Remix (remix-run/remix)
16. Supabase (supabase/supabase)
17. Go
18. Gin (gin-gonic/gin)
19. Echo (labstack/echo)
AI recommended 19 alternatives but never named a16z-infra/ai-getting-started. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of a16z-infra/ai-getting-started?
pass
AI named a16z-infra/ai-getting-started explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts a16z-infra/ai-getting-started in production, what risks or prerequisites should they evaluate first?
pass
AI named a16z-infra/ai-getting-started explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo a16z-infra/ai-getting-started solve, and who is the primary audience?
pass
AI did not name a16z-infra/ai-getting-started — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

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HTML

<a href="https://repogeo.com/en/r/a16z-infra/ai-getting-started"><img src="https://repogeo.com/badge/a16z-infra/ai-getting-started.svg" alt="RepoGEO" /></a>

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a16z-infra/ai-getting-started — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite