RRepoGEO

REPOGEO REPORT · LITE

OpenAutoCoder/Agentless

Default branch main · commit 5ce5888b · scanned 5/21/2026, 3:38:15 PM

GitHub: 2,053 stars · 230 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 OpenAutoCoder/Agentless, 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 to clarify its role as a code repair tool

    Why:

    CURRENT
    Agentless is an *agentless* approach to automatically solve software development problems.
    COPY-PASTE FIX
    Agentless is an *agentless* approach and **tool** designed to automatically solve software development problems, focusing on automated code repair and patch validation.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2407.01489
  • mediumtopics#3
    Add more specific topics related to automated code repair and bug fixing

    Why:

    CURRENT
    agent, artificial-intelligence, llm, software-development
    COPY-PASTE FIX
    agent, artificial-intelligence, llm, software-development, code-repair, bug-fixing, automated-testing, swe-bench

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 OpenAutoCoder/Agentless
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GitHub Copilot Chat
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GitHub Copilot Chat · recommended 1×
  2. GitHub Copilot · recommended 1×
  3. Cursor IDE · recommended 1×
  4. OpenAI API · recommended 1×
  5. Google Gemini API · recommended 1×
  • CATEGORY QUERY
    How can I automate software bug fixing and development tasks using LLMs without complex agents?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot Chat
    2. GitHub Copilot
    3. Cursor IDE
    4. OpenAI API
    5. Google Gemini API
    6. Google Cloud Vertex AI
    7. Tabnine
    8. Codeium

    AI recommended 8 alternatives but never named OpenAutoCoder/Agentless. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best tools for automated code repair and patch validation in software projects?
    you: not recommended
    AI recommended (in order):
    1. DeepSource
    2. Snyk Code
    3. SonarQube/SonarCloud
    4. Codiga
    5. Semgrep
    6. RefactorGPT
    7. ESLint
    8. Black
    9. Clang-Tidy

    AI recommended 9 alternatives but never named OpenAutoCoder/Agentless. 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 OpenAutoCoder/Agentless?
    pass
    AI named OpenAutoCoder/Agentless explicitly

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

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

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

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MARKDOWN (README)
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OpenAutoCoder/Agentless — 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