RRepoGEO

REPOGEO REPORT · LITE

Doriandarko/make-it-heavy

Default branch main · commit d293cce8 · scanned 6/26/2026, 2:52:54 PM

GitHub: 1,117 stars · 183 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)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 Doriandarko/make-it-heavy, 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 specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    python, multi-agent-system, ai-agents, grok-heavy, openrouter, llm, generative-ai, framework
  • highreadme#2
    Reposition the README's opening to explicitly state its purpose and counter misinterpretations

    Why:

    CURRENT
    A Python framework to emulate **Grok heavy** functionality using a powerful multi-agent system.
    COPY-PASTE FIX
    Make It heavy is a powerful Python framework for advanced multi-agent AI orchestration, directly emulating **Grok heavy** functionality. This project is *not* for generating large dummy files; instead, it deploys specialized AI agents in parallel to deliver comprehensive, multi-perspective analysis on any query.
  • mediumhomepage#3
    Add a homepage URL to the 'About' section

    Why:

    COPY-PASTE FIX
    https://github.com/Doriandarko/make-it-heavy

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 Doriandarko/make-it-heavy
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. CrewAI · recommended 1×
  3. AutoGen · recommended 1×
  4. Haystack · recommended 1×
  5. LlamaIndex · recommended 1×
  • CATEGORY QUERY
    What Python framework helps deploy multiple AI agents for comprehensive, multi-perspective analysis?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. CrewAI
    3. AutoGen
    4. Haystack
    5. LlamaIndex
    6. Open Interpreter

    AI recommended 6 alternatives but never named Doriandarko/make-it-heavy. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a Python library to orchestrate parallel AI agents for complex problem solving.
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. CrewAI (joaomdmoura/crewAI)
    3. AutoGen (microsoft/autogen)
    4. Haystack (deepset-ai/haystack)
    5. Marvin (PrefectHQ/marvin)
    6. Rivet (Ironclad/rivet)
    7. PyTorch (pytorch/pytorch)
    8. TensorFlow (tensorflow/tensorflow)

    AI recommended 8 alternatives but never named Doriandarko/make-it-heavy. 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 Doriandarko/make-it-heavy?
    pass
    AI did not name Doriandarko/make-it-heavy — 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 Doriandarko/make-it-heavy in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Doriandarko/make-it-heavy 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 Doriandarko/make-it-heavy solve, and who is the primary audience?
    pass
    AI named Doriandarko/make-it-heavy explicitly

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

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Doriandarko/make-it-heavy — 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