RRepoGEO

REPOGEO REPORT · LITE

Doriandarko/make-it-heavy

Default branch main · commit d293cce8 · scanned 5/15/2026, 7:52:26 PM

GitHub: 1,113 stars · 184 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 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
  • highreadme#1
    Clarify the meaning of 'heavy' in the README to prevent misinterpretation

    Why:

    CURRENT
    A Python framework to emulate **Grok heavy** functionality using a powerful multi-agent system. Built on OpenRouter's API, Make It heavy delivers comprehensive, multi-perspective analysis through intelligent agent orchestration.
    COPY-PASTE FIX
    A Python framework to emulate **Grok heavy** functionality using a powerful multi-agent system. Built on OpenRouter's API, Make It heavy delivers comprehensive, multi-perspective analysis through intelligent agent orchestration. Here, 'heavy' refers to the deep, multi-faceted AI analysis provided by parallel agents, not file size manipulation.
  • hightopics#2
    Add relevant topics to categorize the repository correctly

    Why:

    COPY-PASTE FIX
    multi-agent-system, ai-agents, grok-heavy, python, openrouter, generative-ai, llm-orchestration, agent-framework
  • mediumlicense#3
    Add a section to the README clarifying the existing license

    Why:

    COPY-PASTE FIX
    ## License
    
    This project is released under [describe your specific license(s) here, e.g., 'a custom license combining elements of X and Y', or 'the terms outlined in the LICENSE file']. Please refer to the `LICENSE` file for full details.

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 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. AutoGen · recommended 2×
  3. CrewAI · recommended 2×
  4. Haystack · recommended 1×
  5. LlamaIndex · recommended 1×
  • CATEGORY QUERY
    How can I deploy multiple AI agents for comprehensive, multi-perspective problem solving?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. AutoGen
    3. CrewAI
    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
    What Python frameworks enable orchestrating multiple AI agents for complex analysis tasks?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Haystack (deepset/haystack)
    3. CrewAI
    4. AutoGen
    5. Marvin
    6. DSPy

    AI recommended 6 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 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?

  • 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