RRepoGEO

REPOGEO REPORT · LITE

WujiangXu/A-mem

Default branch main · commit 0c8039f2 · scanned 5/31/2026, 4:48:11 PM

GitHub: 897 stars · 92 forks

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 WujiangXu/A-mem, 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 improve categorization

    Why:

    COPY-PASTE FIX
    llm-agents, agentic-memory, large-language-models, ai-agents, neurips, research-code, memory-systems
  • highreadme#2
    Reposition README H1 to explicitly state purpose and domain

    Why:

    CURRENT
    # Agentic Memory 🧠
    COPY-PASTE FIX
    # A-Mem: Reproduction Code for Agentic Memory for LLM Agents 🧠
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/WujiangXu/A-mem-sys

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 WujiangXu/A-mem
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. Chroma · recommended 2×
  4. Pinecone · recommended 2×
  5. Weaviate · recommended 2×
  • CATEGORY QUERY
    How to build LLM agents with more sophisticated and organized memory capabilities?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. MemGPT
    4. Haystack
    5. Chroma
    6. Pinecone
    7. Weaviate

    AI recommended 7 alternatives but never named WujiangXu/A-mem. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What advanced memory systems support dynamic organization and flexible interaction for AI agents?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Pinecone
    3. Chroma
    4. Weaviate
    5. LlamaIndex
    6. Redis
    7. RedisJSON
    8. RedisGraph
    9. RedisGears
    10. Neo4j
    11. Milvus
    12. Zilliz Cloud
    13. Faiss

    AI recommended 13 alternatives but never named WujiangXu/A-mem. 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 WujiangXu/A-mem?
    pass
    AI named WujiangXu/A-mem explicitly

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

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

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

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WujiangXu/A-mem — 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