RRepoGEO

REPOGEO REPORT · LITE

MoonshotAI/kosong

Default branch main · commit 1ddade6c · scanned 6/12/2026, 6:34:06 AM

GitHub: 520 stars · 52 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
0 pass · 2 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 MoonshotAI/kosong, 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 README H1 to clearly state Kosong's purpose

    Why:

    CURRENT
    # Kosong
    COPY-PASTE FIX
    # Kosong: The LLM Abstraction Layer for Modern AI Agent Applications
  • mediumlicense#2
    Add a LICENSE file to the repository

    Why:

    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).
  • lowreadme#3
    Expand README content with key details

    Why:

    COPY-PASTE FIX
    Add sections to the README covering key features, installation instructions, basic usage examples, and contribution guidelines.

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 MoonshotAI/kosong
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. Haystack · recommended 2×
  4. Microsoft Semantic Kernel · recommended 2×
  5. OpenAI Python Library · recommended 1×
  • CATEGORY QUERY
    What are some good LLM abstraction layers for developing modern AI agent applications?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. OpenAI Python Library
    5. Microsoft Semantic Kernel
    6. AgentVerse

    AI recommended 6 alternatives but never named MoonshotAI/kosong. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Which SDKs provide a flexible framework for building AI agents with various LLM backends?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Microsoft Semantic Kernel
    4. Haystack
    5. OpenAI Assistants API

    AI recommended 5 alternatives but never named MoonshotAI/kosong. 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
    warn

    Suggestion:

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 MoonshotAI/kosong?
    pass
    AI named MoonshotAI/kosong explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of MoonshotAI/kosong. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/MoonshotAI/kosong.svg)](https://repogeo.com/en/r/MoonshotAI/kosong)
HTML
<a href="https://repogeo.com/en/r/MoonshotAI/kosong"><img src="https://repogeo.com/badge/MoonshotAI/kosong.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

MoonshotAI/kosong — 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