RRepoGEO

REPOGEO REPORT · LITE

Tencent/TencentDB-Agent-Memory

Default branch main · commit c13d0200 · scanned 5/19/2026, 12:22:02 PM

GitHub: 3,449 stars · 268 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
22 /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
1 / 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 Tencent/TencentDB-Agent-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 README H1 and opening paragraph to clarify purpose

    Why:

    CURRENT
    ### Agents remember,Humans innovate.
    COPY-PASTE FIX
    ### TencentDB Agent Memory: Fully Local Long-Term Memory for AI Agents

This project provides a fully local, 4-tier progressive pipeline for long-term memory in AI Agents, distinct from TencentDB database management solutions. It operates with zero external API dependencies.
  • mediumreadme#2
    Add a 'Comparison with Alternatives' section to the README

    Why:

    COPY-PASTE FIX
    ## 💡 Comparison with Alternatives

Unlike general-purpose vector databases (e.g., ChromaDB, FAISS) or broad AI frameworks (e.g., LangChain, LlamaIndex), TencentDB Agent Memory is purpose-built for AI Agents. It offers a unique 4-tier progressive pipeline for fully local long-term memory, emphasizing symbolic short-term memory and layered long-term memory to reduce token usage and improve task success without external API dependencies.
  • lowreadme#3
    Add a 'Use Cases & Audience' section to the README

    Why:

    COPY-PASTE FIX
    ## 🎯 Use Cases & Audience

TencentDB Agent Memory is designed for developers and researchers building advanced AI agents who require robust, fully local long-term memory solutions. It is ideal for scenarios where reducing token usage, improving task success rates, and maintaining data locality are critical, especially for complex conversational AI and autonomous agent systems.

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 Tencent/TencentDB-Agent-Memory
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Annoy
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Annoy · recommended 2×
  2. ChromaDB · recommended 1×
  3. FAISS · recommended 1×
  4. SQLite · recommended 1×
  5. Hugging Face Transformers · recommended 1×
  • CATEGORY QUERY
    How can I implement fully local long-term memory for my AI agents without external APIs?
    you: not recommended
    AI recommended (in order):
    1. ChromaDB
    2. FAISS
    3. SQLite
    4. Hugging Face Transformers
    5. NumPy
    6. Annoy
    7. NMSLIB
    8. Annoy
    9. Hnswlib
    10. DiskANN

    AI recommended 10 alternatives but never named Tencent/TencentDB-Agent-Memory. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help AI agents manage conversational memory to reduce token usage and improve task success?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Redis
    4. Pinecone
    5. Weaviate

    AI recommended 5 alternatives but never named Tencent/TencentDB-Agent-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
    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 Tencent/TencentDB-Agent-Memory?
    pass
    AI did not name Tencent/TencentDB-Agent-Memory — 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?

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

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite