RRepoGEO

REPOGEO REPORT · LITE

alibaba/havenask

Default branch main · commit 26bf4c15 · scanned 5/20/2026, 10:22:12 PM

GitHub: 1,829 stars · 347 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 alibaba/havenask, 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

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

OVERALL DIRECTION
  • mediumreadme#1
    Strengthen README introduction with explicit category keywords

    Why:

    CURRENT
    As a search engine developed by Alibaba Group, Havenask is a large-scale distributed information search system widely used within Alibaba Group. It provides the search services for business across the Alibaba Group such as Taobao, Tmall, Cainiao, Amap, Ele.me, and global services. It offers high-performance and easy-to-use search services with low costs. Havenask also provides flexible customization and development capabilities. Its algorithms can be fast iterated. This way, Havenask enables you to develop intelligent search service tailored for your business and empower business growth.
    COPY-PASTE FIX
    Havenask is a high-performance, distributed search engine and information retrieval system, developed by Alibaba Group for large-scale real-time indexing and querying of billions of records. Widely used across Alibaba's core services like Taobao and Tmall, it provides scalable, low-cost search capabilities for e-commerce and other demanding applications, offering flexible customization and rapid algorithm iteration.

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 alibaba/havenask
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
elastic/elasticsearch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. elastic/elasticsearch · recommended 2×
  2. opensearch-project/OpenSearch · recommended 2×
  3. elastic/kibana · recommended 1×
  4. elastic/logstash · recommended 1×
  5. apache/solr · recommended 1×
  • CATEGORY QUERY
    What are the best distributed search engines for real-time indexing billions of records?
    you: not recommended
    AI recommended (in order):
    1. Elasticsearch (elastic/elasticsearch)
    2. Kibana (elastic/kibana)
    3. Logstash (elastic/logstash)
    4. Apache Solr (apache/solr)
    5. OpenSearch (opensearch-project/OpenSearch)
    6. Apache Druid (apache/druid)
    7. ClickHouse (ClickHouse/ClickHouse)

    AI recommended 7 alternatives but never named alibaba/havenask. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to build a custom, high-performance search service for e-commerce or large applications?
    you: not recommended
    AI recommended (in order):
    1. Elasticsearch (elastic/elasticsearch)
    2. Apache Solr
    3. OpenSearch (opensearch-project/OpenSearch)
    4. Meilisearch (meilisearch/meilisearch)
    5. Algolia
    6. Typesense (typesense/typesense)

    AI recommended 6 alternatives but never named alibaba/havenask. 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 alibaba/havenask?
    pass
    AI named alibaba/havenask explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of alibaba/havenask. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
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alibaba/havenask — 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