RRepoGEO

REPOGEO REPORT · LITE

Q00/ouroboros

Default branch main · commit b7c1ceb3 · scanned 6/27/2026, 8:51:43 PM

GitHub: 4,732 stars · 466 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
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 Q00/ouroboros, 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
    Clarify the core purpose immediately after the main title in README

    Why:

    CURRENT
    <p align="center">
  <strong>O U R O B O R O S</strong>
  <br/><br/>
  ◯ ─────────── ◯
  <br/>
</p>

<p align="center">
  <strong>Stop prompting. Start specifying.</strong>
  <br/>
  <sub>The <strong>Agent OS</strong> for replayable, specification-first AI coding workflows</sub>
</p>
    COPY-PASTE FIX
    <p align="center">
  <strong>O U R O B O R O S</strong>
  <br/><br/>
  ◯ ─────────── ◯
  <br/>
</p>
<p align="center">
  <strong>An Agent OS for reproducible, specification-first AI coding workflows.</strong>
</p>
<p align="center">
  <strong>Stop prompting. Start specifying.</strong>
  <br/>
  <sub>The <strong>Agent OS</strong> for replayable, specification-first AI coding workflows</sub>
</p>
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Add a relevant URL (e.g., project website, documentation, or a more detailed GitHub Pages site) to the 'Homepage' field in your repository settings.
  • mediumtopics#3
    Expand repository topics for better specificity

    Why:

    CURRENT
    agent-os, ai-agent, llm-orchestration, llm-runtime, python
    COPY-PASTE FIX
    agent-os, ai-agent, llm-orchestration, llm-runtime, python, reproducible-ai, specification-driven-ai, ai-workflow, agent-framework, code-generation

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 Q00/ouroboros
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. Haystack · recommended 2×
  4. OpenAI Assistants API · recommended 2×
  5. AutoGen · recommended 1×
  • CATEGORY QUERY
    How can I build robust AI agents with reproducible, specification-driven coding workflows?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGen
    5. Mirasol
    6. OpenAI Assistants API

    AI recommended 6 alternatives but never named Q00/ouroboros. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help orchestrate multiple LLMs for generating and verifying code effectively?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. OpenAI Assistants API
    5. Microsoft Semantic Kernel
    6. AutoGPT
    7. BabyAGI
    8. Guidance

    AI recommended 8 alternatives but never named Q00/ouroboros. 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 Q00/ouroboros?
    pass
    AI named Q00/ouroboros explicitly

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

  • If a team adopts Q00/ouroboros in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Q00/ouroboros 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 Q00/ouroboros solve, and who is the primary audience?
    pass
    AI named Q00/ouroboros explicitly

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

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Q00/ouroboros — 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