RRepoGEO

REPOGEO REPORT · LITE

KimMeen/Time-LLM

Default branch main · commit b13e881f · scanned 5/25/2026, 3:12:30 AM

GitHub: 2,651 stars · 466 forks

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 KimMeen/Time-LLM, 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
    Add a concise problem/solution statement to the README introduction

    Why:

    CURRENT
    The README currently starts with the title and a block of external links.
    COPY-PASTE FIX
    Insert a concise paragraph immediately after the main title/links, e.g., "Time-LLM is a novel framework that enables Large Language Models (LLMs) to perform accurate time series forecasting by reprogramming their capabilities. This repository provides the official implementation, allowing researchers and practitioners to leverage LLMs for complex time series analysis tasks."
  • mediumtopics#2
    Expand topics with application-focused keywords

    Why:

    CURRENT
    cross-modal-learning, cross-modality, deep-learning, language-model, large-language-models, machine-learning, multimodal-deep-learning, multimodal-time-series, prompt-tuning, time-series, time-series-analysis, time-series-forecast, time-series-forecasting
    COPY-PASTE FIX
    Add "llm-forecasting", "time-series-llm", "forecasting-framework", "ai-forecasting" to the existing topics.
  • mediumreadme#3
    Add a 'Key Features' or 'What Time-LLM Offers' section

    Why:

    COPY-PASTE FIX
    Add a bulleted 'Key Features' section early in the README, detailing what the framework provides (e.g., "Reprograms LLMs for time series tasks", "Supports various forecasting benchmarks", "Provides code for data preparation and model training").

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 KimMeen/Time-LLM
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 2×
  2. Chronos (AWS) · recommended 1×
  3. Lag-Llama (Nixtla) · recommended 1×
  4. OpenAI GPT-4 / GPT-3.5 · recommended 1×
  5. Google Gemini / PaLM · recommended 1×
  • CATEGORY QUERY
    How can I leverage large language models for accurate time series prediction?
    you: not recommended
    AI recommended (in order):
    1. Chronos (AWS)
    2. Lag-Llama (Nixtla)
    3. OpenAI GPT-4 / GPT-3.5
    4. Google Gemini / PaLM
    5. Hugging Face Transformers
    6. TimeGPT (Nixtla)

    AI recommended 6 alternatives but never named KimMeen/Time-LLM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools enable adapting pre-trained language models for time series analysis tasks?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PyTorch Forecasting
    3. GluonTS
    4. TimeGPT
    5. Keras-Tuner
    6. Optuna
    7. Ray Tune
    8. Fast.ai
    9. TensorFlow Probability

    AI recommended 9 alternatives but never named KimMeen/Time-LLM. 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 KimMeen/Time-LLM?
    pass
    AI named KimMeen/Time-LLM explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
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