RRepoGEO

REPOGEO REPORT · LITE

verygoodplugins/automem

Default branch main · commit edd97421 · scanned 6/9/2026, 5:37:00 AM

GitHub: 748 stars · 94 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 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 verygoodplugins/automem, 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
  • highreadme#1
    Reposition the core value proposition immediately after the H1

    Why:

    CURRENT
    The current README structure where the H1 is followed by a problem statement, and the core value proposition is in a preceding centered paragraph.
    COPY-PASTE FIX
    # AutoMem

Long-term memory for AI assistants. Graph + vector. Runs on your hardware.

Your AI forgets between sessions. RAG dumps documents that look similar. Vector databases match keywords but miss meaning. None of them learn.
  • mediumreadme#2
    Add an explicit 'What is AutoMem?' section early in the README

    Why:

    COPY-PASTE FIX
    ## What is AutoMem?

AutoMem is a self-hosted graph-vector memory service designed to give AI assistants durable, relational long-term memory. Unlike simple vector databases, AutoMem stores typed relationships alongside embeddings, allowing for contextual and relational recall that mimics human memory. It enables AI to learn and retrieve not just matching data, but also the context, alternatives, and related decisions.
  • mediumabout#3
    Refine the GitHub 'About' description for stronger keyword alignment

    Why:

    CURRENT
    AutoMem is a graph-vector memory service that gives AI assistants durable, relational memory:
    COPY-PASTE FIX
    AutoMem: A graph-vector memory service providing durable, relational long-term memory for AI assistants and models.

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 verygoodplugins/automem
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Weaviate
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Weaviate · recommended 2×
  2. Chroma · recommended 2×
  3. PostgreSQL with pgvector · recommended 1×
  4. Pinecone · recommended 1×
  5. Redis with Redis Stack · recommended 1×
  • CATEGORY QUERY
    How to give my AI assistant persistent, relational long-term memory across sessions?
    you: not recommended
    AI recommended (in order):
    1. PostgreSQL with pgvector
    2. Pinecone
    3. Weaviate
    4. Chroma
    5. Redis with Redis Stack
    6. MongoDB Atlas

    AI recommended 6 alternatives but never named verygoodplugins/automem. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools provide durable, relational memory for AI models, beyond simple vector search?
    you: not recommended
    AI recommended (in order):
    1. PostgreSQL
    2. pg_embedding
    3. pgvector
    4. Neo4j
    5. Amazon Neptune
    6. ArangoDB
    7. Weaviate
    8. Chroma
    9. Elasticsearch
    10. OpenSearch
    11. Milvus
    12. Zilliz Cloud

    AI recommended 12 alternatives but never named verygoodplugins/automem. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 verygoodplugins/automem?
    pass
    AI named verygoodplugins/automem explicitly

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

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