RRepoGEO

REPOGEO REPORT · LITE

Dataojitori/nocturne_memory

Default branch main · commit beee74a3 · scanned 6/19/2026, 6:26:53 AM

GitHub: 1,213 stars · 148 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
40 /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
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 Dataojitori/nocturne_memory, 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 English README's opening to explicitly differentiate from databases

    Why:

    COPY-PASTE FIX
    In the English README (README_EN.md), add a clear, concise statement in the first paragraph or immediately after the main heading that positions Nocturne Memory as a *specialized AI memory system* distinct from traditional databases. For example: 'Nocturne Memory is not just another database; it's a dedicated Long-Term Memory Server for MCP Agents, designed to provide persistent, structured, and cognitive memory capabilities far beyond what generic vector RAG or traditional databases offer.'
  • hightopics#2
    Remove generic database terms from topics list

    Why:

    CURRENT
    agentic-ai, ai-identity, ai-memory, artificial-intelligence, claude, claude-code, digital-soul, gemini-cli, llm, long-term-memory, mcp, mcp-server, postgresql, python, rag, second-brain, sqlite
    COPY-PASTE FIX
    agentic-ai, ai-identity, ai-memory, artificial-intelligence, claude, claude-code, digital-soul, gemini-cli, llm, long-term-memory, mcp, mcp-server, python, rag, second-brain
  • mediumcomparison#3
    Add a dedicated comparison section in the English README

    Why:

    COPY-PASTE FIX
    Add a new section to the English README (README_EN.md), perhaps titled 'Nocturne Memory vs. Traditional Databases & Vector RAG' or 'Why Not Just a Database?', explaining the fundamental differences and unique advantages for AI agents. This section should clearly articulate why Nocturne Memory is a superior choice for AI agent memory compared to generic database solutions.

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 Dataojitori/nocturne_memory
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PostgreSQL
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PostgreSQL · recommended 2×
  2. Pinecone · recommended 1×
  3. Chroma · recommended 1×
  4. Redis · recommended 1×
  5. MongoDB · recommended 1×
  • CATEGORY QUERY
    How can I give my AI agents persistent, session-agnostic memory and a consistent identity?
    you: not recommended
    AI recommended (in order):
    1. Pinecone
    2. Chroma
    3. Redis
    4. PostgreSQL
    5. MongoDB
    6. LangChain
    7. LlamaIndex

    AI recommended 7 alternatives but never named Dataojitori/nocturne_memory. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an alternative to vector RAG for complex, structured long-term memory in AI agents.
    you: not recommended
    AI recommended (in order):
    1. Neo4j
    2. Amazon Neptune
    3. ArangoDB (arangodb/arangodb)
    4. PostgreSQL
    5. pg_trgm
    6. PostGIS (postgis/postgis)
    7. OrientDB (orientechnologies/orientdb)
    8. Apache Jena (apache/jena)
    9. Stardog
    10. GraphDB
    11. MongoDB (mongodb/mongo)
    12. Elasticsearch (elastic/elasticsearch)

    AI recommended 12 alternatives but never named Dataojitori/nocturne_memory. 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 Dataojitori/nocturne_memory?
    pass
    AI named Dataojitori/nocturne_memory explicitly

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

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

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

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Dataojitori/nocturne_memory — 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