RRepoGEO

REPOGEO REPORT · LITE

samvallad33/vestige

Default branch main · commit 241dfdd6 · scanned 6/11/2026, 1:36:53 AM

GitHub: 549 stars · 56 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 samvallad33/vestige, 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 README's opening to clarify its core purpose for AI agents

    Why:

    CURRENT
    # Vestige

### Local cognitive memory for MCP-compatible AI agents.
    COPY-PASTE FIX
    # Vestige: Cognitive Memory for AI Agents

### Local, inspectable memory for MCP-compatible AI agents, built on FSRS-6 spaced repetition and neuroscience principles. Not a password manager or generic vector database.
  • mediumcomparison#2
    Add a comparison section to the README to differentiate from alternatives

    Why:

    COPY-PASTE FIX
    ## Vestige vs. Other Memory Systems

Vestige is designed specifically for AI agent cognitive memory, combining spaced repetition (FSRS-6) with neuroscience-inspired modules for long-term knowledge retention and decision recall. Unlike generic vector databases (e.g., Pinecone, Weaviate, Qdrant, LlamaIndex), Vestige focuses on *cognitive processes* like consolidation and forgetting curves, not just semantic similarity. It also differs from human-centric spaced repetition systems (e.g., Anki, SuperMemo) by integrating directly with AI agents via MCP for automated, context-aware memory management.
  • lowtopics#3
    Refine repository topics to emphasize AI agents and remove ambiguous terms

    Why:

    CURRENT
    ai-memory, claude, cognitive-science, cursor, embeddings, fsrs, local-first, long-term-memory, mcp, mcp-server, neuroscience, onnx, rust, security, spaced-repetition, sqlite, sveltekit, threejs, vscode, webgpu
    COPY-PASTE FIX
    ai-memory, ai-agents, claude, cognitive-science, cursor, embeddings, fsrs, local-first, long-term-memory, mcp, mcp-server, neuroscience, onnx, rust, spaced-repetition, sqlite, sveltekit, threejs, vscode, webgpu

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 samvallad33/vestige
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. Pinecone · recommended 1×
  3. Weaviate · recommended 1×
  4. Qdrant · recommended 1×
  5. LlamaIndex · recommended 1×
  • CATEGORY QUERY
    How to give AI agents persistent, inspectable memory for project decisions and long-term context?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Pinecone
    3. Weaviate
    4. Qdrant
    5. LlamaIndex
    6. Chroma
    7. FAISS
    8. Milvus
    9. MemGPT
    10. PostgreSQL
    11. pgvector
    12. MongoDB
    13. Atlas Vector Search
    14. Neo4j
    15. Grakn
    16. TypeDB
    17. KnowledgeGraphMemory

    AI recommended 17 alternatives but never named samvallad33/vestige. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a local-first spaced repetition system for AI agent cognitive memory and knowledge retention.
    you: not recommended
    AI recommended (in order):
    1. Anki
    2. SuperMemo
    3. Mnemosyne
    4. RemNote
    5. Obsidian

    AI recommended 5 alternatives but never named samvallad33/vestige. 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 samvallad33/vestige?
    pass
    AI named samvallad33/vestige explicitly

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

  • If a team adopts samvallad33/vestige in production, what risks or prerequisites should they evaluate first?
    pass
    AI named samvallad33/vestige 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 samvallad33/vestige solve, and who is the primary audience?
    pass
    AI named samvallad33/vestige explicitly

    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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MARKDOWN (README)
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samvallad33/vestige — 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
samvallad33/vestige — RepoGEO report