RRepoGEO

REPOGEO REPORT · LITE

callstackincubator/ai

Default branch main · commit 8c200af8 · scanned 6/28/2026, 11:37:23 AM

GitHub: 1,352 stars · 52 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
33 /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
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 callstackincubator/ai, 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
    Reposition the README's opening paragraph to emphasize LLM execution

    Why:

    CURRENT
    A collection of on-device AI primitives for React Native with first-class Vercel AI SDK support. Run AI models directly on users' devices for privacy-preserving, low-latency inference without server costs.
    COPY-PASTE FIX
    React Native AI is a collection of on-device LLM execution primitives for React Native, offering first-class compatibility with the Vercel AI SDK. It enables running large language models directly on users' devices for privacy-preserving, low-latency inference without server costs.
  • mediumtopics#2
    Add more specific topics to highlight Vercel AI SDK and mobile LLM focus

    Why:

    CURRENT
    ai, llm, on-device-ai, react-native
    COPY-PASTE FIX
    ai, llm, on-device-ai, react-native, vercel-ai-sdk, mobile-llm, edge-ai
  • mediumreadme#3
    Add a 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to your README, for example, after 'Features', titled 'Comparison' or 'Why React Native AI?' with content like: 'Unlike general-purpose ML runtimes such as TensorFlow Lite or Core ML, React Native AI is specifically designed for React Native applications, providing high-level primitives for on-device LLM execution with seamless Vercel AI SDK compatibility. It offers a higher-level abstraction and direct integration with the Vercel AI SDK, streamlining development for mobile LLM experiences.'

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 callstackincubator/ai
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Core ML
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Core ML · recommended 2×
  2. TensorFlow Lite · recommended 2×
  3. MLC LLM · recommended 1×
  4. Transformers.js · recommended 1×
  5. ONNX Runtime Mobile · recommended 1×
  • CATEGORY QUERY
    How can I execute large language models directly on-device within a React Native app?
    you: not recommended
    AI recommended (in order):
    1. MLC LLM
    2. Transformers.js
    3. ONNX Runtime Mobile
    4. Core ML
    5. TensorFlow Lite
    6. MediaPipe

    AI recommended 6 alternatives but never named callstackincubator/ai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a privacy-preserving AI solution for React Native, compatible with popular AI SDKs?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Lite
    2. TensorFlow Federated
    3. react-native-tensorflow-lite
    4. Core ML
    5. ML Kit
    6. react-native-core-ml
    7. react-native-firebase
    8. OpenMMLab
    9. ONNX
    10. ONNX Runtime
    11. Privy
    12. SEAL
    13. HEaaN

    AI recommended 13 alternatives but never named callstackincubator/ai. 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 callstackincubator/ai?
    pass
    AI did not name callstackincubator/ai — 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?

  • If a team adopts callstackincubator/ai in production, what risks or prerequisites should they evaluate first?
    pass
    AI named callstackincubator/ai 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 callstackincubator/ai solve, and who is the primary audience?
    pass
    AI named callstackincubator/ai explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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callstackincubator/ai — 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