RRepoGEO

REPOGEO REPORT · LITE

github/gh-aw

Default branch main · commit f3e4f74f · scanned 5/29/2026, 6:36:33 AM

GitHub: 4,535 stars · 408 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 github/gh-aw, 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 the README's opening paragraph to clarify its unique value

    Why:

    CURRENT
    Write agentic workflows in natural language markdown, and run them in GitHub Actions.
    COPY-PASTE FIX
    Define and run powerful AI agentic workflows directly within GitHub Actions using natural language markdown. This `gh` extension empowers you to automate complex repository tasks with large language models like Copilot, Claude, Codex, and Gemini, going beyond traditional CI/CD.
  • hightopics#2
    Refine repository topics to emphasize AI agents and natural language automation

    Why:

    CURRENT
    actions, cai, ci, claude-code, codex, copilot, gh-extension, github-actions
    COPY-PASTE FIX
    ai-agents, llm-automation, natural-language-workflows, github-actions, gh-extension, copilot, claude, openai, gemini, workflow-automation
  • mediumfaq#3
    Add an FAQ entry comparing gh-aw to generic alternatives

    Why:

    COPY-PASTE FIX
    Add a new entry to the 'FAQ' section: 'How does GitHub Agentic Workflows compare to traditional GitHub Actions or no-code automation tools like Zapier/Make?'

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 github/gh-aw
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GitHub Actions
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. GitHub Actions · recommended 2×
  2. Zapier · recommended 2×
  3. Make · recommended 2×
  4. OpenAI GPT-4 · recommended 1×
  5. Claude 3 Opus · recommended 1×
  • CATEGORY QUERY
    How can I automate repository tasks using AI agents defined in natural language markdown?
    you: not recommended
    AI recommended (in order):
    1. GitHub Actions
    2. OpenAI GPT-4
    3. Claude 3 Opus
    4. Google Gemini Advanced
    5. Python
    6. JavaScript
    7. LangChain (langchain-ai/langchain)
    8. GitHub API
    9. Autogen (microsoft/autogen)
    10. Pipedream
    11. Zapier
    12. Make
    13. OpenAI
    14. GitHub
    15. Flask (pallets/flask)
    16. Node.js (nodejs/node)
    17. GitPython (gitpython-developers/GitPython)

    AI recommended 17 alternatives but never named github/gh-aw. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools allow integrating large language models for intelligent workflow automation in CI/CD?
    you: not recommended
    AI recommended (in order):
    1. GitHub Actions
    2. OpenAI API
    3. Anthropic API
    4. Hugging Face API
    5. GitLab CI/CD
    6. Jenkins
    7. Azure DevOps Pipelines
    8. Azure OpenAI Service
    9. CircleCI
    10. Argo Workflows (argoproj/argo-workflows)
    11. Zapier
    12. Make

    AI recommended 12 alternatives but never named github/gh-aw. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 github/gh-aw?
    pass
    AI named github/gh-aw explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of github/gh-aw. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite