RRepoGEO

REPOGEO REPORT · LITE

cchenax/px-kvstore

Default branch main · commit 163f058c · scanned 6/4/2026, 4:53:25 PM

GitHub: 876 stars · 98 forks

AI VISIBILITY SCORE
30 /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
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 cchenax/px-kvstore, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    key-value-store, kv-store, in-memory, llm-caching, ai-inference, replication, distributed-systems, go
  • highlicense#2
    Add a LICENSE file and update the About section

    Why:

    CURRENT
    (no LICENSE file detected)
    COPY-PASTE FIX
    Add a `LICENSE` file (e.g., MIT or Apache-2.0) to the repository root, then update the 'About' section on GitHub with the chosen license name.
  • mediumreadme#3
    Strengthen README's opening for AI-specific use cases

    Why:

    CURRENT
    A lightweight, high-performance KV engine for deterministic LLM caching and fast local inference experimentation.
    COPY-PASTE FIX
    PX-KVStore: The specialized, high-performance key-value engine for **deterministic LLM caching and accelerated local AI inference experimentation.**

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 cchenax/px-kvstore
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
redis/redis
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. redis/redis · recommended 2×
  2. memcached/memcached · recommended 1×
  3. apache/ignite · recommended 1×
  4. aerospike/aerospike-server · recommended 1×
  5. hazelcast/hazelcast · recommended 1×
  • CATEGORY QUERY
    Seeking a high-performance in-memory key-value store for LLM caching and AI inference.
    you: not recommended
    AI recommended (in order):
    1. Redis (redis/redis)
    2. Memcached (memcached/memcached)
    3. Apache Ignite (apache/ignite)
    4. Aerospike (aerospike/aerospike-server)
    5. Hazelcast IMDG (hazelcast/hazelcast)

    AI recommended 5 alternatives but never named cchenax/px-kvstore. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are lightweight sharded KV store options for fast local AI experimentation with replication?
    you: not recommended
    AI recommended (in order):
    1. Redis Cluster (redis/redis)
    2. RocksDB (facebook/rocksdb)
    3. TiKV (tikv/tikv)
    4. BadgerDB (dgraph-io/badger)
    5. FoundationDB (apple/foundationdb)

    AI recommended 5 alternatives but never named cchenax/px-kvstore. 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 cchenax/px-kvstore?
    pass
    AI named cchenax/px-kvstore explicitly

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

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

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

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cchenax/px-kvstore — 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