RRepoGEO

REPOGEO REPORT · LITE

Open-Curiosity/gini-agent

Default branch main · commit 2065132e · scanned 6/28/2026, 3:46:49 PM

GitHub: 730 stars · 176 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 Open-Curiosity/gini-agent, 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
    Clarify the README's opening sentence to emphasize its 'local-first runtime' nature

    Why:

    CURRENT
    Gini Agent is a personal agent that remembers, improves, and runs without forcing you to read a log line.
    COPY-PASTE FIX
    Gini Agent is a local-first personal AI agent runtime and system of record that remembers, improves, and runs without forcing you to read a log line.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/Open-Curiosity/gini-agent
  • lowtopics#3
    Add more specific topics related to agent learning and memory management

    Why:

    CURRENT
    agent, agent-runtime, ai-agent, bun, llm, local-first, mcp, nextjs, personal-agent, typescript
    COPY-PASTE FIX
    agent, agent-runtime, ai-agent, bun, llm, local-first, mcp, nextjs, personal-agent, typescript, agent-learning, memory-management, conversation-management

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 Open-Curiosity/gini-agent
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. OpenAI GPT-4 · recommended 1×
  3. Pinecone · recommended 1×
  4. ChromaDB · recommended 1×
  5. OpenAI GPT-3.5 Turbo · recommended 1×
  • CATEGORY QUERY
    How to build a personal AI agent that learns from interactions and remembers past conversations?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. OpenAI GPT-4
    3. Pinecone
    4. ChromaDB
    5. OpenAI GPT-3.5 Turbo
    6. LlamaIndex
    7. Hugging Face Transformers
    8. FAISS
    9. Annoy
    10. Llama 2
    11. Mistral
    12. Mixtral 8x7B
    13. Rasa
    14. Rasa NLU
    15. Rasa Core
    16. Voiceflow

    AI recommended 16 alternatives but never named Open-Curiosity/gini-agent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks enable building local-first personal AI agents with Bun runtime?
    you: not recommended
    AI recommended (in order):
    1. Bun
    2. LangChain.js
    3. LlamaIndex.TS
    4. Ollama
    5. Transformers.js
    6. llama.cpp
    7. text-generation-webui

    AI recommended 7 alternatives but never named Open-Curiosity/gini-agent. 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 Open-Curiosity/gini-agent?
    pass
    AI named Open-Curiosity/gini-agent explicitly

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

  • If a team adopts Open-Curiosity/gini-agent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Open-Curiosity/gini-agent 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 Open-Curiosity/gini-agent solve, and who is the primary audience?
    pass
    AI named Open-Curiosity/gini-agent 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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Open-Curiosity/gini-agent — 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