RRepoGEO

REPOGEO REPORT · LITE

iannuttall/ralph

Default branch main · commit 5bc40254 · scanned 6/2/2026, 3:36:50 AM

GitHub: 927 stars · 90 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 iannuttall/ralph, 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
    Reposition README H1 and opening paragraph to clarify core purpose

    Why:

    CURRENT
    # Ralph

Ralph is a minimal, file‑based agent loop for autonomous coding. Each iteration starts fresh, reads the same on‑disk state, and commits work for one story at a time.
    COPY-PASTE FIX
    # Ralph: A File-Based Autonomous Coding Agent

Ralph is a minimal, file-based agent loop designed for autonomous coding, treating files and Git as its primary memory and state management system.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai-agent, autonomous-coding, agent-loop, generative-ai, file-based, git-based, cli-tool
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root. For example, choose a permissive license like MIT and add the standard MIT license text.

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 iannuttall/ralph
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Significant-Gravitas/AutoGPT
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Significant-Gravitas/AutoGPT · recommended 1×
  2. langchain-ai/langchain · recommended 1×
  3. run-llama/llama_index · recommended 1×
  4. joaomdmoura/crewAI · recommended 1×
  5. yoheinakajima/babyagi · recommended 1×
  • CATEGORY QUERY
    How can I set up an autonomous coding agent that uses local files for state?
    you: not recommended
    AI recommended (in order):
    1. AutoGPT (Significant-Gravitas/AutoGPT)
    2. LangChain (langchain-ai/langchain)
    3. LlamaIndex (run-llama/llama_index)
    4. CrewAI (joaomdmoura/crewAI)
    5. BabyAGI (yoheinakajima/babyagi)
    6. GitPython (gitpython-developers/GitPython)

    AI recommended 6 alternatives but never named iannuttall/ralph. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help manage AI agent development state using git and local files?
    you: not recommended
    AI recommended (in order):
    1. DVC (Data Version Control)
    2. Git LFS (Large File Storage)
    3. MLflow
    4. Neptune.ai
    5. Weights & Biases (W&B)
    6. Pachyderm
    7. Git Submodules/Symlinks

    AI recommended 7 alternatives but never named iannuttall/ralph. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 iannuttall/ralph?
    pass
    AI named iannuttall/ralph explicitly

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

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

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

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iannuttall/ralph — 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