RRepoGEO

REPOGEO REPORT · LITE

TinyAGI/fractals

Default branch main · commit c0d93970 · scanned 6/9/2026, 6:47:45 PM

GitHub: 639 stars · 47 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 TinyAGI/fractals, 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
    ai-agents, orchestration, task-decomposition, agent-swarm, recursive-tasks, generative-ai, workflow-automation
  • highreadme#2
    Clarify the README's main title (H1) to specify the category

    Why:

    CURRENT
    <h1>Fractals 🌀</h1>
    COPY-PASTE FIX
    <h1>Fractals 🌀: Recursive Agentic Task Orchestrator</h1>
  • mediumreadme#3
    Reinforce the project's purpose in the README's opening paragraph

    Why:

    CURRENT
    Give it any high-level task and it grows a self-similar tree of executable subtasks, then runs each leaf in isolated git worktrees with an agent swarm.
    COPY-PASTE FIX
    Give this recursive agentic task orchestrator any high-level task, and it will grow a self-similar tree of executable subtasks, then run each leaf in isolated git worktrees with an AI agent swarm.

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 TinyAGI/fractals
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. AutoGPT · recommended 1×
  4. Microsoft Guidance · recommended 1×
  5. Haystack · recommended 1×
  • CATEGORY QUERY
    How to automatically decompose large tasks into manageable subtasks for AI agents?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGPT
    4. Microsoft Guidance
    5. Haystack
    6. OpenAI Function Calling

    AI recommended 6 alternatives but never named TinyAGI/fractals. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a tool to orchestrate multiple AI agents in isolated execution environments.
    you: not recommended
    AI recommended (in order):
    1. Kubernetes
    2. Ray
    3. Apache Airflow
    4. Metaflow
    5. Prefect
    6. AWS Step Functions
    7. Azure Logic Apps
    8. Google Cloud Workflows

    AI recommended 8 alternatives but never named TinyAGI/fractals. 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 TinyAGI/fractals?
    pass
    AI did not name TinyAGI/fractals — 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 TinyAGI/fractals in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name TinyAGI/fractals — 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?

  • In one sentence, what problem does the repo TinyAGI/fractals solve, and who is the primary audience?
    pass
    AI named TinyAGI/fractals explicitly

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

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TinyAGI/fractals — 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
TinyAGI/fractals — RepoGEO report