RRepoGEO

REPOGEO REPORT · LITE

Marktechpost/AI-Agents-Projects-Tutorials

Default branch main · commit c08fb5d1 · scanned 5/23/2026, 4:03:05 AM

GitHub: 2,613 stars · 577 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
22 /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
1 / 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 Marktechpost/AI-Agents-Projects-Tutorials, 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, prominent H1 to the README emphasizing 'tutorials'

    Why:

    COPY-PASTE FIX
    # AI Agent Tutorials, Implementations, and Notebooks
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT, Apache-2.0, or GPL-3.0) in the repository root to clarify usage rights.
  • mediumabout#3
    Update the About description to highlight its tutorial nature

    Why:

    CURRENT
    Multi-agent systems, memory, planning, reasoning loops
    COPY-PASTE FIX
    Tutorials and implementations for multi-agent systems, memory, planning, and reasoning loops.

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 Marktechpost/AI-Agents-Projects-Tutorials
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. LlamaIndex · recommended 1×
  3. Haystack · recommended 1×
  4. AutoGPT · recommended 1×
  5. OpenAI Assistants API · recommended 1×
  • CATEGORY QUERY
    How to build an advanced AI agent with planning, tool calling, and self-critique capabilities?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGPT
    5. OpenAI Assistants API
    6. CrewAI
    7. Microsoft Semantic Kernel

    AI recommended 7 alternatives but never named Marktechpost/AI-Agents-Projects-Tutorials. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for tutorials on implementing persistent memory for multi-user AI agent applications.
    you: not recommended
    AI recommended (in order):
    1. PostgreSQL
    2. pgvector
    3. Pinecone
    4. Redis
    5. Redis Stack
    6. RedisJSON
    7. RediSearch
    8. RedisGears
    9. MongoDB Atlas
    10. MongoDB
    11. SQLite
    12. FAISS
    13. ChromaDB

    AI recommended 13 alternatives but never named Marktechpost/AI-Agents-Projects-Tutorials. 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 Marktechpost/AI-Agents-Projects-Tutorials?
    pass
    AI did not name Marktechpost/AI-Agents-Projects-Tutorials — 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 Marktechpost/AI-Agents-Projects-Tutorials in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Marktechpost/AI-Agents-Projects-Tutorials 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 Marktechpost/AI-Agents-Projects-Tutorials solve, and who is the primary audience?
    pass
    AI did not name Marktechpost/AI-Agents-Projects-Tutorials — 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?

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Marktechpost/AI-Agents-Projects-Tutorials — 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