RRepoGEO

REPOGEO REPORT · LITE

Emiyaaaaa/HiveMind

Default branch main · commit 41d322f5 · scanned 5/18/2026, 8:13:14 AM

GitHub: 1,004 stars · 92 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
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 Emiyaaaaa/HiveMind, 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
  • highabout#1
    Clarify repository's project name and purpose in the About description

    Why:

    COPY-PASTE FIX
    Emiyaaaaa/HiveMind is AgentFlow: A Python-first runtime layer for multi-agent systems, providing persistent run state, streaming execution events, and a pluggable orchestration interface for frameworks like LangGraph or AutoGen.
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    python, multi-agent-systems, agent-frameworks, runtime, orchestration, persistence, event-streaming, ai-agents, langgraph, autogen, crewai
  • mediumreadme#3
    Strengthen README's opening to clarify 'runtime layer' vs. 'framework'

    Why:

    CURRENT
    AgentFlow provides the runtime infrastructure around multi-agent applications. It does not replace frameworks such as LangGraph, AutoGen or CrewAI. Instead, it gives them a consistent execution model: agents are invoked as runs, runs produce ordered steps and messages, tool calls are recorded, and every state change can be streamed to a client.
    COPY-PASTE FIX
    AgentFlow is a Python-first runtime layer designed to provide robust infrastructure *for* multi-agent systems. Unlike frameworks such as LangGraph, AutoGen, or CrewAI, AgentFlow does not dictate agent orchestration; instead, it offers a consistent execution model with persistent run state, streaming execution events, and a pluggable interface, enabling these frameworks to operate with durable history, ordered steps, and real-time event streaming.

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 Emiyaaaaa/HiveMind
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
akka/akka
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. akka/akka · recommended 1×
  2. dotnet/orleans · recommended 1×
  3. apache/flink · recommended 1×
  4. lagom/lagom · recommended 1×
  5. dapr/dapr · recommended 1×
  • CATEGORY QUERY
    How to build a production-ready multi-agent system with durable state and event streaming?
    you: not recommended
    AI recommended (in order):
    1. Akka (akka/akka)
    2. Microsoft Orleans (dotnet/orleans)
    3. Apache Flink (apache/flink)
    4. Lagom (lagom/lagom)
    5. Dapr (dapr/dapr)
    6. Apache Kafka Streams (apache/kafka)
    7. ksqlDB (confluentinc/ksqldb)
    8. Ray (ray-project/ray)

    AI recommended 8 alternatives but never named Emiyaaaaa/HiveMind. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a Python runtime layer for multi-agent systems with pluggable orchestration and persistence.
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. Haystack (deepset-ai/haystack)
    3. CrewAI (joaomdmoura/crewAI)
    4. AutoGen (microsoft/autogen)
    5. SPADE (javipalanca/spade)
    6. Mesa (projectmesa/mesa)

    AI recommended 6 alternatives but never named Emiyaaaaa/HiveMind. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 Emiyaaaaa/HiveMind?
    pass
    AI named Emiyaaaaa/HiveMind explicitly

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

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

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

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Emiyaaaaa/HiveMind — 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