REPOGEO REPORT · LITE

ax-llm/ax

Default branch main · commit d6417ea9 · scanned 5/17/2026, 5:26:57 AM

GitHub: 2,637 stars · 167 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

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 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 ax-llm/ax, 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

highreadme#1

Strengthen README's opening to explicitly state DSPy-like problem solving

Why:

CURRENT

# Ax — DSPy for TypeScript
Automatic prompt generation, RLM agents, and a single API across 15+ providers. Production-tested.

COPY-PASTE FIX

# Ax — The DSPy Framework for TypeScript
Implement advanced DSPy-like prompt engineering patterns and build robust LLM agents directly in TypeScript. Ax provides automatic prompt generation, RLM agents, and a single API across 15+ providers, all production-tested.

mediumtopics#2

Add specific topics for prompt engineering and LLM agents

Why:

CURRENT

ai, anthropic, claude, cohere, dspy, gemini, google, google-gemini, gpt-4, javascript, large-language-models, llm, nodejs, ollama, openai, opensource, rag, typescript, vectordb, webllm

COPY-PASTE FIX

ai, anthropic, claude, cohere, dspy, gemini, google, google-gemini, gpt-4, javascript, large-language-models, llm, nodejs, ollama, openai, opensource, prompt-engineering, rag, typescript, vectordb, webllm, llm-agents

mediumreadme#3

Add a comparison section to differentiate from broader frameworks

Why:

COPY-PASTE FIX

## Ax vs. Other LLM Frameworks

While frameworks like LangChain.js and LlamaIndex.TS offer broad LLM orchestration, Ax focuses specifically on bringing the declarative, DSPy-inspired programming model to TypeScript. This means Ax prioritizes automatic prompt optimization, structured output, and robust agent construction through signatures, offering a more focused and type-safe approach for complex prompt engineering patterns compared to general-purpose libraries.

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 ax-llm/ax

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

langchain-ai/langchainjs

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

langchain-ai/langchainjs · recommended 1×
run-llama/llama_index · recommended 1×
openai/openai-node · recommended 1×
promptfoo/promptfoo · recommended 1×
colinhacks/zod · recommended 1×

CATEGORY QUERY
How to implement DSPy-like prompt engineering patterns in a TypeScript application?
you: not recommended
AI recommended (in order):
1. LangChain.js (langchain-ai/langchainjs)
2. LlamaIndex.TS (run-llama/llama_index)
3. OpenAI SDK (openai/openai-node)
4. Promptfoo (promptfoo/promptfoo)
5. Zod (colinhacks/zod)
6. TypeChat (microsoft/TypeChat)
AI recommended 6 alternatives but never named ax-llm/ax. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What framework allows building LLM agents with a single API across providers in Node.js?
you: not recommended
AI recommended (in order):
1. LangChain.js
2. LlamaIndex.TS
3. Agent Protocol
4. OpenAI SDK
5. LiteLLM
AI recommended 5 alternatives but never named ax-llm/ax. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
pass
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 ax-llm/ax?
pass
AI named ax-llm/ax explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts ax-llm/ax in production, what risks or prerequisites should they evaluate first?
pass
AI named ax-llm/ax 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 ax-llm/ax solve, and who is the primary audience?
pass
AI named ax-llm/ax explicitly
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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Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite