RRepoGEO

REPOGEO REPORT · LITE

alash3al/stash

Default branch main · commit c10117b4 · scanned 6/10/2026, 5:01:59 AM

GitHub: 712 stars · 34 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 alash3al/stash, 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 sentence to clarify specific domain

    Why:

    CURRENT
    # Stash

**Your AI has amnesia. We fixed it.**

Every LLM starts every conversation from zero. Stash gives your agent persistent memory — it remembers, recalls, consolidates, and learns across sessions. No more explaining yourself from scratch.
    COPY-PASTE FIX
    # Stash: Persistent Memory Layer for AI Agents

**Your AI has amnesia. We fixed it.** Stash is a persistent memory layer specifically designed for AI agents, storing episodes, facts, and working context in Postgres. It remembers, recalls, consolidates, and learns across sessions, so your LLM never starts a conversation from zero.
  • mediumtopics#2
    Add more specific AI memory and technology topics

    Why:

    CURRENT
    ai, ai-agents, ai-memory, memory
    COPY-PASTE FIX
    ai, ai-agents, ai-memory, memory, long-term-memory, episodic-memory, agent-memory, postgres, pgvector
  • lowreadme#3
    Add a 'Why Stash?' or 'Comparison' section to README

    Why:

    COPY-PASTE FIX
    ## Why Stash?

Unlike generic key-value stores, Stash is purpose-built for AI agent memory, offering persistent storage for episodes, facts, and working context in Postgres. Compared to vector databases, Stash provides a structured approach to memory management, focusing on recall and consolidation for conversational AI agents rather than just semantic search.

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 alash3al/stash
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Weaviate
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Weaviate · recommended 2×
  2. LangChain · recommended 2×
  3. Pinecone · recommended 1×
  4. Redis · recommended 1×
  5. PostgreSQL · recommended 1×
  • CATEGORY QUERY
    How to give my AI agent persistent memory across multiple conversations?
    you: not recommended
    AI recommended (in order):
    1. Pinecone
    2. Weaviate
    3. Redis
    4. PostgreSQL
    5. MongoDB
    6. Faiss
    7. LangChain

    AI recommended 7 alternatives but never named alash3al/stash. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good self-hosted solutions for managing AI agent long-term memory with Postgres?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. pgvector
    3. LlamaIndex
    4. SuperDuperDB
    5. Weaviate
    6. Postgres
    7. Qdrant
    8. SQLAlchemy
    9. Django ORM
    10. Hugging Face Transformers
    11. OpenAI API

    AI recommended 11 alternatives but never named alash3al/stash. 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 alash3al/stash?
    pass
    AI named alash3al/stash explicitly

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

  • If a team adopts alash3al/stash in production, what risks or prerequisites should they evaluate first?
    pass
    AI named alash3al/stash 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 alash3al/stash solve, and who is the primary audience?
    pass
    AI named alash3al/stash explicitly

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

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alash3al/stash — RepoGEO report