RRepoGEO

REPOGEO REPORT · LITE

im4codes/imcodes

Default branch master · commit a4120afd · scanned 6/23/2026, 3:01:56 PM

GitHub: 512 stars · 67 forks

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 im4codes/imcodes, 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
    Explicitly define "IM" and reposition the README's opening statement

    Why:

    CURRENT
    **The IM for agents. Shared memory, managed MCP tools, supervised execution, and cross-agent audit across AI providers.**
    COPY-PASTE FIX
    **IM.codes is an Instant Messaging (IM) platform specifically designed for AI agents. It provides shared memory, managed MCP tools, supervised execution, and cross-agent audit capabilities across various AI providers.**
  • mediumtopics#2
    Add more specific topics for multi-agent systems and orchestration

    Why:

    CURRENT
    ai, ai-agents, automation, claude, claude-code, codex, codex-cli, gemini, gemini-cli, instant-messaging, openai, openclaw
    COPY-PASTE FIX
    ai, ai-agents, automation, claude, claude-code, codex, codex-cli, gemini, gemini-cli, instant-messaging, openai, openclaw, multi-agent-systems, agent-orchestration, agent-collaboration, llm-agents, agent-memory, agent-context, ai-workflow
  • lowreadme#3
    Add a dedicated "Why IM.codes?" or "Comparison" section to the README

    Why:

    COPY-PASTE FIX
    ## Why IM.codes?
    
    IM.codes stands apart by offering a dedicated, real-time communication and collaboration layer for AI agents. Unlike generic data stores (e.g., Redis, PostgreSQL) or broad workflow orchestrators (e.g., LangChain, Airflow), IM.codes provides agent-specific shared memory, managed tool access, and supervised execution across diverse AI providers, enabling true multi-agent workflows and cross-agent auditing.

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 im4codes/imcodes
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Redis
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Redis · recommended 1×
  2. Apache Kafka · recommended 1×
  3. PostgreSQL · recommended 1×
  4. FaunaDB · recommended 1×
  5. LangChain · recommended 1×
  • CATEGORY QUERY
    How can I enable shared context and memory for multiple AI agents across different platforms?
    you: not recommended
    AI recommended (in order):
    1. Redis
    2. Apache Kafka
    3. PostgreSQL
    4. FaunaDB
    5. LangChain
    6. RabbitMQ
    7. Google Cloud Pub/Sub
    8. AWS SQS/SNS
    9. Azure Service Bus

    AI recommended 9 alternatives but never named im4codes/imcodes. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools facilitate supervised execution and cross-agent auditing for autonomous AI development workflows?
    you: not recommended
    AI recommended (in order):
    1. MLflow
    2. Kubeflow Pipelines
    3. Apache Airflow
    4. Prefect
    5. Weights & Biases
    6. DVC
    7. Metaflow

    AI recommended 7 alternatives but never named im4codes/imcodes. 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 im4codes/imcodes?
    pass
    AI named im4codes/imcodes explicitly

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

  • If a team adopts im4codes/imcodes in production, what risks or prerequisites should they evaluate first?
    pass
    AI named im4codes/imcodes 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 im4codes/imcodes solve, and who is the primary audience?
    pass
    AI named im4codes/imcodes 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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  • Brand-free category queries5 vs 2 in Lite
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