RRepoGEO

REPOGEO REPORT · LITE

MoonshotAI/Kimi-K2.5

Default branch master · commit 3e60763b · scanned 6/29/2026, 6:02:48 AM

GitHub: 2,077 stars · 262 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
35 /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
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/Kimi-K2.5, 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 specific topics to the repository

    Why:

    COPY-PASTE FIX
    multimodal-ai, agentic-ai, large-language-models, vision-language-model, llm, open-source-llm, conversational-ai, ai-agents
  • highhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://www.kimi.com
  • mediumreadme#3
    Clarify the existing license(s) in the README

    Why:

    COPY-PASTE FIX
    This project is released under the terms specified in the [LICENSE](LICENSE) file. Please review the file for full details on usage and distribution.

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/Kimi-K2.5
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LLaVA
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LLaVA · recommended 1×
  2. MiniGPT-4 · recommended 1×
  3. InstructBLIP · recommended 1×
  4. OpenFlamingo · recommended 1×
  5. Qwen-VL · recommended 1×
  • CATEGORY QUERY
    Looking for an open-source multimodal agentic model for integrating vision and language understanding.
    you: not recommended
    AI recommended (in order):
    1. LLaVA
    2. MiniGPT-4
    3. InstructBLIP
    4. OpenFlamingo
    5. Qwen-VL
    6. Fuyu-8B

    AI recommended 6 alternatives but never named MoonshotAI/Kimi-K2.5. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best open-source models for building conversational AI with advanced agentic capabilities?
    you: not recommended
    AI recommended (in order):
    1. Llama 3
    2. Mixtral 8x7B
    3. Gemma
    4. Mistral 7B
    5. Falcon 180B

    AI recommended 5 alternatives but never named MoonshotAI/Kimi-K2.5. 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 MoonshotAI/Kimi-K2.5?
    pass
    AI named MoonshotAI/Kimi-K2.5 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/Kimi-K2.5 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named MoonshotAI/Kimi-K2.5 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/Kimi-K2.5 solve, and who is the primary audience?
    pass
    AI named MoonshotAI/Kimi-K2.5 explicitly

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

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MoonshotAI/Kimi-K2.5 — 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