RRepoGEO

REPOGEO REPORT · LITE

nmslib/hnswlib

Default branch master · commit d9b3608c · scanned 5/28/2026, 12:47:14 PM

GitHub: 5,240 stars · 825 forks

AI VISIBILITY SCORE
85 /100
Healthy
Category recall
2 / 2
Avg rank #2.0 when recommended
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 nmslib/hnswlib, 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
  • mediumreadme#1
    Refine the README's opening paragraph to highlight core value and dynamic updates

    Why:

    CURRENT
    # Hnswlib - fast approximate nearest neighbor search
Header-only C++ HNSW implementation with python bindings, insertions and updates.
    COPY-PASTE FIX
    # Hnswlib - fast approximate nearest neighbor search
Hnswlib is a high-performance, header-only C++ library with Python bindings for fast Approximate Nearest Neighbor (ANN) search. It implements the Hierarchical Navigable Small World (HNSW) algorithm, offering an exceptional balance of high recall and fast query times, especially for dynamic datasets requiring efficient insertions and updates.
  • lowcomparison#2
    Add a 'Comparison with Alternatives' section to the README

    Why:

    COPY-PASTE FIX
    ## Comparison with Alternatives
Hnswlib stands out among Approximate Nearest Neighbor (ANN) libraries like Faiss, Annoy, and ScaNN due to its exceptional balance of high recall (accuracy) and fast query times, particularly in high-dimensional vector spaces. A key differentiator is its robust support for dynamic index updates (insertions and deletions) without requiring a full index rebuild, making it ideal for evolving datasets.

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
2 / 2
100% of queries surface nmslib/hnswlib
Avg rank
#2.0
Lower is better. #1 = top recommendation.
Share of voice
18%
Of all named tools, what % are you?
Top rival
Faiss
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Faiss · recommended 2×
  2. Annoy · recommended 2×
  3. ScaNN · recommended 2×
  4. NMSLIB · recommended 1×
  5. FLANN · recommended 1×
  • CATEGORY QUERY
    What are the best libraries for fast approximate nearest neighbor search in C++ or Python?
    you: #2
    AI recommended (in order):
    1. Faiss
    2. Hnswlib ← you
    3. Annoy
    4. ScaNN
    5. NMSLIB
    6. FLANN
    Show full AI answer
  • CATEGORY QUERY
    Seeking a high-performance approximate nearest neighbor library that supports dynamic index updates.
    you: #2
    AI recommended (in order):
    1. Faiss
    2. Hnswlib ← you
    3. Annoy
    4. ScaNN
    5. Milvus
    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 nmslib/hnswlib?
    pass
    AI named nmslib/hnswlib explicitly

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

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

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

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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite