RRepoGEO

REPOGEO REPORT · LITE

Git-on-my-level/codex-autorunner

Default branch main · commit 4b815217 · scanned 6/2/2026, 5:16:24 AM

GitHub: 808 stars · 67 forks

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 Git-on-my-level/codex-autorunner, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    A meta-harness for coordinating and automating long-running tasks for multiple AI coding agents (e.g., Codex, Hermes, OpenCode), managing their work queues and notifying you when stuck.
  • mediumreadme#2
    Add a 'How CAR Differs' section to the README

    Why:

    COPY-PASTE FIX
    ## How CAR Differs

Unlike general agent frameworks such as LangChain or CrewAI, CAR is not an agent builder; it's a meta-harness designed to orchestrate *existing* coding agents (like Codex, Hermes, or OpenCode) through long-horizon development tasks. While tools like Apache Airflow or Temporal manage general workflows, CAR is purpose-built for the unique challenges of managing iterative code generation, execution, and debugging cycles across multiple AI coding agents.

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 Git-on-my-level/codex-autorunner
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AutoGPT
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. AutoGPT · recommended 1×
  2. CrewAI · recommended 1×
  3. LangChain · recommended 1×
  4. OpenAI Assistants API · recommended 1×
  5. MetaGPT · recommended 1×
  • CATEGORY QUERY
    How to automate long-horizon development tasks using multiple AI coding agents?
    you: not recommended
    AI recommended (in order):
    1. AutoGPT
    2. CrewAI
    3. LangChain
    4. OpenAI Assistants API
    5. MetaGPT
    6. Smol-developer
    7. BabyAGI

    AI recommended 7 alternatives but never named Git-on-my-level/codex-autorunner. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a system to coordinate autonomous coding agents and manage their work queues.
    you: not recommended
    AI recommended (in order):
    1. Apache Airflow (apache/airflow)
    2. Temporal (temporalio/temporal)
    3. Celery (celery/celery)
    4. Prefect (PrefectHQ/prefect)
    5. AWS Step Functions
    6. Kubernetes (kubernetes/kubernetes)
    7. KEDA (kedacore/keda)

    AI recommended 7 alternatives but never named Git-on-my-level/codex-autorunner. 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 Git-on-my-level/codex-autorunner?
    pass
    AI named Git-on-my-level/codex-autorunner explicitly

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

  • If a team adopts Git-on-my-level/codex-autorunner in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Git-on-my-level/codex-autorunner 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 Git-on-my-level/codex-autorunner solve, and who is the primary audience?
    pass
    AI named Git-on-my-level/codex-autorunner explicitly

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

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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite
Git-on-my-level/codex-autorunner — RepoGEO report