RRepoGEO

REPOGEO REPORT · LITE

XTraceAI/xtrace-sdk

Default branch main · commit 0f8522e4 · scanned 7/1/2026, 5:43:43 AM

GitHub: 956 stars · 250 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)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 XTraceAI/xtrace-sdk, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening to clearly state the SDK's purpose

    Why:

    CURRENT
    Every vector database on the market requires you to hand your data to a third party in plaintext. XTrace doesn't. Your documents and embedding vectors are encrypted **on your machine** before anything is transmitted.
    COPY-PASTE FIX
    The XTraceAI/xtrace-sdk is a Python client for XTrace, the encrypted vector database. It enables developers to store and query vector embeddings and documents with end-to-end, client-side encryption, ensuring data privacy by keeping your information encrypted on your machine.
  • mediumreadme#2
    Add a 'Key Features' section to highlight differentiators

    Why:

    COPY-PASTE FIX
    ## Key Features

*   **Client-Side Encryption:** All data (documents, embeddings) is encrypted on your machine before transmission.
*   **End-to-End Privacy:** Your data remains encrypted even during server-side storage and nearest-neighbor search.
*   **Encrypted Vector Search (x-vec):** Securely store and query text chunks.
*   **Encrypted Agent Memory (x-mem):** (Coming soon) Secure memory for AI agents.

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 XTraceAI/xtrace-sdk
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Pinecone
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Pinecone · recommended 2×
  2. microsoft/SEAL · recommended 1×
  3. zama-ai/concrete-ml · recommended 1×
  4. MongoDB · recommended 1×
  5. PostgreSQL · recommended 1×
  • CATEGORY QUERY
    How to store and query vector embeddings while maintaining end-to-end encryption?
    you: not recommended
    AI recommended (in order):
    1. Microsoft SEAL (microsoft/SEAL)
    2. Concrete ML (zama-ai/concrete-ml)
    3. MongoDB
    4. PostgreSQL
    5. AWS KMS
    6. Azure Key Vault
    7. Google Cloud KMS
    8. Intel SGX
    9. Azure Confidential Computing
    10. Google Confidential VMs
    11. Milvus (milvus-io/milvus)
    12. Pinecone

    AI recommended 12 alternatives but never named XTraceAI/xtrace-sdk. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a vector database that encrypts data on the client-side before storage.
    you: not recommended
    AI recommended (in order):
    1. Qdrant
    2. OpenSSL
    3. Google Tink
    4. Pinecone
    5. Weaviate
    6. Milvus
    7. Zilliz Cloud
    8. Faiss
    9. AWS S3
    10. Microsoft SEAL
    11. HElib

    AI recommended 11 alternatives but never named XTraceAI/xtrace-sdk. 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 XTraceAI/xtrace-sdk?
    pass
    AI named XTraceAI/xtrace-sdk explicitly

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

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

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

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XTraceAI/xtrace-sdk — 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