RRepoGEO

REPOGEO REPORT · LITE

fetchai/innovation-lab-examples

Default branch main · commit 52906943 · scanned 6/21/2026, 7:07:03 AM

GitHub: 1,125 stars · 79 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
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 fetchai/innovation-lab-examples, 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 to the repository

    Why:

    COPY-PASTE FIX
    autonomous-agents, multi-agent-systems, fetch-ai, uagents, agentverse, llm-agents, web3-agents, payment-integration, code-examples, real-world-applications
  • highreadme#2
    Refine README's opening sentence to differentiate from simulation environments

    Why:

    CURRENT
    A curated collection of **production-quality agent examples** built with Fetch.ai technologies — uAgents, ASI:One, Agentverse, A2A protocol, MCP, and more.
    COPY-PASTE FIX
    A curated collection of **production-quality, real-world agent examples** for building and deploying autonomous multi-agent systems with Fetch.ai technologies — uAgents, ASI:One, Agentverse, A2A protocol, MCP, and more. Unlike simulation environments, these examples focus on practical, integrated implementations for real-world applications.
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://fetch.ai/innovation-lab (or relevant project/documentation page)

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 fetchai/innovation-lab-examples
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PettingZoo
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PettingZoo · recommended 1×
  2. MAgent · recommended 1×
  3. OpenSpiel · recommended 1×
  4. Gym-ANM · recommended 1×
  5. Multi-Agent Particle Environment (MPE) · recommended 1×
  • CATEGORY QUERY
    Where can I find practical examples for building autonomous multi-agent systems?
    you: not recommended
    AI recommended (in order):
    1. PettingZoo
    2. MAgent
    3. OpenSpiel
    4. Gym-ANM
    5. Multi-Agent Particle Environment (MPE)
    6. Unity ML-Agents Toolkit
    7. MASON

    AI recommended 7 alternatives but never named fetchai/innovation-lab-examples. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Show me code examples for integrating AI, payments, and Web3 into agent applications.
    you: not recommended
    AI recommended (in order):
    1. OpenAI API (GPT-3.5/GPT-4)
    2. Hugging Face Transformers
    3. Google Cloud AI Platform / Vertex AI
    4. Stripe
    5. Coinbase Commerce
    6. Metamask SDK / WalletConnect
    7. Alchemy Pay
    8. Ethers.js
    9. Web3.js
    10. MetaMask
    11. Alchemy / Infura
    12. The Graph

    AI recommended 12 alternatives but never named fetchai/innovation-lab-examples. 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 fetchai/innovation-lab-examples?
    pass
    AI named fetchai/innovation-lab-examples explicitly

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

  • If a team adopts fetchai/innovation-lab-examples in production, what risks or prerequisites should they evaluate first?
    pass
    AI named fetchai/innovation-lab-examples 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 fetchai/innovation-lab-examples solve, and who is the primary audience?
    pass
    AI did not name fetchai/innovation-lab-examples — 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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fetchai/innovation-lab-examples — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite