RRepoGEO

REPOGEO REPORT · LITE

supermemoryai/opencode-supermemory

Default branch main · commit 61ad679e · scanned 5/9/2026, 9:12:36 AM

GitHub: 1,148 stars · 83 forks

AI VISIBILITY SCORE
28 /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
2 / 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 supermemoryai/opencode-supermemory, 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
  • hightopics#1
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    ["opencode-plugin", "ai-coding-assistant", "long-term-memory", "agent-memory", "developer-tools", "rag", "persistent-memory"]
  • highreadme#2
    Strengthen README's opening to clarify its role for AI coding assistants

    Why:

    CURRENT
    # opencode-supermemory
    
    OpenCode plugin for persistent memory using Supermemory.
    
    Your agent remembers what you tell it - across sessions, across projects.
    COPY-PASTE FIX
    # opencode-supermemory: Persistent Memory Plugin for AI Coding Assistants
    
    Empower your AI coding assistant with long-term memory. This OpenCode plugin uses Supermemory to enable your agent to remember past interactions, context, and project details across sessions and projects, making it truly conversational and effective in your developer environment.
  • mediumlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    (Create a LICENSE file in the repository root with your chosen open-source license, e.g., MIT or Apache-2.0. For example, for MIT:
    
    MIT License
    
    Copyright (c) [year] [fullname]
    
    Permission is hereby granted, free of charge, to any person obtaining a copy
    of this software and associated documentation files (the "Software"), to deal
    in the Software without restriction, including without limitation the rights
    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
    copies of the Software, and to permit persons to whom the Software is
    furnished to do so, subject to the following conditions:
    
    The above copyright notice and this permission notice shall be included in all
    copies or substantial portions of the Software.
    
    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
    SOFTWARE.)

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 supermemoryai/opencode-supermemory
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. Pinecone · recommended 2×
  3. Weaviate · recommended 2×
  4. LlamaIndex · recommended 2×
  5. Qdrant · recommended 2×
  • CATEGORY QUERY
    How can I enable my AI coding assistant to remember past interactions and context?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Pinecone
    3. Weaviate
    4. ChromaDB
    5. LlamaIndex
    6. Milvus
    7. Qdrant
    8. Redis
    9. PostgreSQL
    10. pgvector
    11. Faiss

    AI recommended 11 alternatives but never named supermemoryai/opencode-supermemory. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What plugins offer long-term conversational memory for my developer AI environment?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Redis
    3. PostgreSQL
    4. SQLAlchemy
    5. PgVector
    6. Pinecone
    7. Weaviate
    8. Qdrant
    9. MongoDB
    10. LlamaIndex
    11. Chroma
    12. Faiss
    13. MemGPT
    14. OpenAI Assistants API

    AI recommended 14 alternatives but never named supermemoryai/opencode-supermemory. 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 supermemoryai/opencode-supermemory?
    pass
    AI did not name supermemoryai/opencode-supermemory — 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 supermemoryai/opencode-supermemory in production, what risks or prerequisites should they evaluate first?
    pass
    AI named supermemoryai/opencode-supermemory 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 supermemoryai/opencode-supermemory solve, and who is the primary audience?
    pass
    AI named supermemoryai/opencode-supermemory explicitly

    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
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