RRepoGEO

REPOGEO REPORT · LITE

mainframecomputer/orchestra

Default branch main · commit 945d0dd1 · scanned 6/1/2026, 12:11:38 AM

GitHub: 754 stars · 68 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 mainframecomputer/orchestra, 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 for LLM agentic frameworks

    Why:

    COPY-PASTE FIX
    llm, multi-agent, agentic-framework, ai-agents, orchestration, python, large-language-models, generative-ai
  • highreadme#2
    Clarify project domain in README's Overview section

    Why:

    CURRENT
    Mainframe-Orchestra is a lightweight, open-source agentic framework for building LLM-based pipelines and multi-agent teams.
    COPY-PASTE FIX
    Mainframe-Orchestra is a lightweight, open-source agentic framework for building LLM-based pipelines and multi-agent teams. It is a general-purpose orchestrator for AI agents and is not tied to traditional mainframe systems.
  • mediumreadme#3
    Clarify license details in README

    Why:

    COPY-PASTE FIX
    This project is released under the terms specified in the [LICENSE](LICENSE) file. Please refer to the file for full details on the applicable license(s).

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 mainframecomputer/orchestra
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. LlamaIndex · recommended 2×
  5. Haystack · recommended 2×
  • CATEGORY QUERY
    How to build intelligent multi-agent systems for complex problem-solving using various LLMs?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. AutoGen
    3. CrewAI
    4. LlamaIndex
    5. Haystack
    6. OpenAI Assistants API
    7. BabyAGI
    8. Auto-GPT

    AI recommended 8 alternatives but never named mainframecomputer/orchestra. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What framework helps orchestrate multiple AI agents with custom tools and streaming capabilities?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGen
    5. CrewAI
    6. Marvin

    AI recommended 6 alternatives but never named mainframecomputer/orchestra. 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 mainframecomputer/orchestra?
    pass
    AI named mainframecomputer/orchestra explicitly

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

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

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

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mainframecomputer/orchestra — 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