RRepoGEO

REPOGEO REPORT · LITE

badlogic/lemmy

Default branch main · commit 92e4ba60 · scanned 6/27/2026, 4:07:24 AM

GitHub: 1,630 stars · 305 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)

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

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 badlogic/lemmy, 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

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

OVERALL DIRECTION
  • highabout#1
    Update the repository description to match the README's core purpose

    Why:

    CURRENT
    Wrapper around tool using LLMs for agentic workflows
    COPY-PASTE FIX
    A TypeScript ecosystem for building AI applications with unified LLM interfaces, terminal UIs, and practical tools.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).

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 badlogic/lemmy
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchainjs
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchainjs · recommended 1×
  2. run-llama/LlamaIndexTS · recommended 1×
  3. openai/openai-node · recommended 1×
  4. anthropics/anthropic-sdk-typescript · recommended 1×
  5. google/generative-ai-js · recommended 1×
  • CATEGORY QUERY
    How to build AI applications in TypeScript with a unified interface for multiple LLM providers?
    you: not recommended
    AI recommended (in order):
    1. LangChain.js (langchain-ai/langchainjs)
    2. LlamaIndex.TS (run-llama/LlamaIndexTS)
    3. OpenAI SDK (openai/openai-node)
    4. Anthropic SDK (anthropics/anthropic-sdk-typescript)
    5. Google Generative AI SDK (google/generative-ai-js)
    6. Hugging Face Transformers.js (xenova/transformers.js)
    7. Axios/Fetch

    AI recommended 7 alternatives but never named badlogic/lemmy. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a TypeScript library to create interactive terminal UIs for CLI tools.
    you: not recommended
    AI recommended (in order):
    1. Ink (vadimdemedes/ink)
    2. Blessed (chjj/blessed)
    3. Command-Line-Interface (CLI)
    4. Inquirer.js (SBoudrias/Inquirer.js)
    5. Prompts (terkelg/prompts)

    AI recommended 5 alternatives but never named badlogic/lemmy. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 badlogic/lemmy?
    pass
    AI named badlogic/lemmy explicitly

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

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

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

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badlogic/lemmy — 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