RRepoGEO

REPOGEO REPORT · LITE

apoorvumang/prompt-lookup-decoding

Default branch main · commit cada4fe6 · scanned 6/2/2026, 8:43:02 PM

GitHub: 611 stars · 28 forks

AI VISIBILITY SCORE
23 /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
2 / 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 apoorvumang/prompt-lookup-decoding, 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
    Reposition the README H1 to clearly state the project's purpose and category

    Why:

    CURRENT
    # Prompt Lookup Decoding
    COPY-PASTE FIX
    # Prompt Lookup Decoding: Accelerate LLM Inference for Input-Grounded Tasks
  • mediumlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root and populate it with the text of your chosen open-source license (e.g., MIT, Apache-2.0).

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 apoorvumang/prompt-lookup-decoding
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
vLLM
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. vLLM · recommended 2×
  2. DeepSpeed-MII · recommended 2×
  3. TensorRT-LLM · recommended 2×
  4. llama.cpp · recommended 2×
  5. TGI · recommended 1×
  • CATEGORY QUERY
    How can I accelerate large language model inference for input-grounded generation tasks?
    you: not recommended
    AI recommended (in order):
    1. vLLM
    2. DeepSpeed-MII
    3. TensorRT-LLM
    4. TGI
    5. OpenVINO
    6. ONNX Runtime
    7. llama.cpp

    AI recommended 7 alternatives but never named apoorvumang/prompt-lookup-decoding. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for LLM decoding techniques that boost speed without sacrificing output quality.
    you: not recommended
    AI recommended (in order):
    1. Google's Speculative Decoding
    2. Microsoft's Medusa
    3. FlashAttention
    4. FlashAttention-2
    5. bitsandbytes
    6. AWQ
    7. GPTQ
    8. llama.cpp
    9. vLLM
    10. TensorRT-LLM
    11. DeepSpeed-MII
    12. Hugging Face Transformers

    AI recommended 12 alternatives but never named apoorvumang/prompt-lookup-decoding. 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 apoorvumang/prompt-lookup-decoding?
    pass
    AI named apoorvumang/prompt-lookup-decoding explicitly

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

  • If a team adopts apoorvumang/prompt-lookup-decoding in production, what risks or prerequisites should they evaluate first?
    pass
    AI named apoorvumang/prompt-lookup-decoding 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 apoorvumang/prompt-lookup-decoding solve, and who is the primary audience?
    pass
    AI did not name apoorvumang/prompt-lookup-decoding — 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?

Embed your GEO score

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MARKDOWN (README)
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apoorvumang/prompt-lookup-decoding — 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