RRepoGEO

REPOGEO REPORT · LITE

maze-agent/Maze

Default branch main · commit 8c15ee1e · scanned 6/15/2026, 2:47:34 AM

GitHub: 523 stars · 14 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 maze-agent/Maze, 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
    Add a clear, disambiguating introductory sentence to the README

    Why:

    CURRENT
    The README currently starts with a large H2 and then a "News" section.
    COPY-PASTE FIX
    Maze is a distributed framework for LLM agents, *not* a tool for pathfinding or reinforcement learning in mazes. It provides a robust, scalable, and fault-tolerant platform for building and orchestrating complex LLM agent workflows.
  • highreadme#2
    Move core value proposition above the 'News' section in README

    Why:

    CURRENT
    The README excerpt shows "News" immediately after the title and links.
    COPY-PASTE FIX
    Reorganize the README to place a clear, concise section (e.g., "What is Maze?", "Key Features") explaining its purpose, benefits (scalability, fault tolerance, orchestration for LLM agents), and target audience *before* the "News" section. This section should clearly state it's for "scalable and fault-tolerant systems for managing multiple LLM agents" and "orchestrating complex LLM agent workflows".
  • mediumreadme#3
    Add a 'Why Maze?' or 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    Add a section titled "Why Maze?" or "Maze vs. [Competitors]" that highlights Maze's unique strengths (e.g., native distributed architecture, fault tolerance, production readiness for LLM agents) compared to popular LLM agent frameworks like LangChain or LlamaIndex, or how it complements them.

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 maze-agent/Maze
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. LlamaIndex · recommended 2×
  3. Kubernetes · recommended 1×
  4. Ray · recommended 1×
  5. Apache Kafka · recommended 1×
  • CATEGORY QUERY
    How to build a scalable and fault-tolerant system for managing multiple LLM agents?
    you: not recommended
    AI recommended (in order):
    1. Kubernetes
    2. Ray
    3. Apache Kafka
    4. Redis
    5. Prometheus
    6. Grafana
    7. LangChain
    8. LlamaIndex
    9. PostgreSQL
    10. PgBouncer

    AI recommended 10 alternatives but never named maze-agent/Maze. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help orchestrate complex LLM agent workflows with robust error handling?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Microsoft Semantic Kernel
    4. Haystack
    5. AutoGPT
    6. Prefect
    7. Apache Airflow

    AI recommended 7 alternatives but never named maze-agent/Maze. 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 maze-agent/Maze?
    pass
    AI named maze-agent/Maze explicitly

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

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

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

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maze-agent/Maze — 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