RRepoGEO

REPOGEO REPORT · LITE

jihoo-kim/awesome-production-llm

Default branch main · commit dd3b086f · scanned 6/12/2026, 1:27:54 AM

GitHub: 522 stars · 74 forks

AI VISIBILITY SCORE
22 /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
1 / 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 jihoo-kim/awesome-production-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

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

OVERALL DIRECTION
  • highreadme#1
    Rephrase the README's introductory sentence to emphasize it's an 'awesome list'

    Why:

    CURRENT
    This repository contains a curated list of awesome open-source projects for production large language models.
    COPY-PASTE FIX
    This is an awesome list: a curated collection of open-source projects and libraries for building and deploying Large Language Models (LLMs) in production environments.
  • mediumhomepage#2
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/jihoo-kim/awesome-production-llm

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 jihoo-kim/awesome-production-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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 1×
  2. vLLM · recommended 1×
  3. TGI (Text Generation Inference) · recommended 1×
  4. OpenVINO · recommended 1×
  5. ONNX Runtime · recommended 1×
  • CATEGORY QUERY
    What open-source libraries are available for deploying large language models into production environments?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. vLLM
    3. TGI (Text Generation Inference)
    4. OpenVINO
    5. ONNX Runtime
    6. DeepSpeed
    7. TensorRT-LLM

    AI recommended 7 alternatives but never named jihoo-kim/awesome-production-llm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for tools to efficiently manage and monitor LLM inference and serving in production.
    you: not recommended
    AI recommended (in order):
    1. MLflow (mlflow/mlflow)
    2. Arize AI
    3. LangSmith
    4. Prometheus (prometheus/prometheus)
    5. Grafana (grafana/grafana)
    6. Datadog
    7. Seldon Core (SeldonIO/seldon-core)
    8. Weights & Biases

    AI recommended 8 alternatives but never named jihoo-kim/awesome-production-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
    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 jihoo-kim/awesome-production-llm?
    pass
    AI did not name jihoo-kim/awesome-production-llm — 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 jihoo-kim/awesome-production-llm in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jihoo-kim/awesome-production-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 jihoo-kim/awesome-production-llm solve, and who is the primary audience?
    pass
    AI did not name jihoo-kim/awesome-production-llm — 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?

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jihoo-kim/awesome-production-llm — 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