RRepoGEO

REPOGEO REPORT · LITE

githubnext/agentics

Default branch main · commit c02eadfc · scanned 6/1/2026, 6:57:08 AM

GitHub: 736 stars · 105 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 githubnext/agentics, 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
  • highreadme#1
    Clarify README H1 and opening paragraph to emphasize agentic solutions

    Why:

    CURRENT
    # ✨ The Agentics

A sample family of reusable GitHub Agentic Workflows.
    COPY-PASTE FIX
    # ✨ The Agentics: A Collection of Reusable GitHub Agentic Workflows

Agentics provides a powerful collection of pre-built, reusable GitHub Agentic Workflows designed to automate and enhance repository maintenance, fault analysis, and code review. These solutions are built using the [GitHub Agentic Workflows (gh-aw)](https://github.com/github/gh-aw) framework, leveraging AI agents to perform complex tasks like issue triage, CI optimization, and bug fixing, making software development more efficient and enjoyable.
  • mediumabout#2
    Enhance About description for clarity and impact

    Why:

    CURRENT
    A sample pack of GitHub Agentic Workflows!
    COPY-PASTE FIX
    A powerful collection of reusable GitHub Agentic Workflows for repository maintenance, CI optimization, and code review, built on the gh-aw framework.

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 githubnext/agentics
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GitHub Actions · recommended 1×
  2. probot/probot · recommended 1×
  3. Dependabot · recommended 1×
  4. getsentry/sentry · recommended 1×
  5. Zapier · recommended 1×
  • CATEGORY QUERY
    Automate GitHub repository maintenance, including issue triage, bug fixes, and activity summaries.
    you: not recommended
    AI recommended (in order):
    1. GitHub Actions
    2. Probot (probot/probot)
    3. Dependabot
    4. Sentry (getsentry/sentry)
    5. Zapier
    6. Make
    7. Mermaid (mermaid-js/mermaid)

    AI recommended 7 alternatives but never named githubnext/agentics. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I automatically investigate CI failures and optimize GitHub Actions for cost and speed?
    you: not recommended
    AI recommended (in order):
    1. actions/setup-node (actions/setup-node)
    2. actions/setup-python (actions/setup-python)
    3. actions/cache (actions/cache)
    4. BuildPulse
    5. Harness
    6. Datadog CI Visibility
    7. New Relic CI/CD Observability

    AI recommended 7 alternatives but never named githubnext/agentics. 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 githubnext/agentics?
    pass
    AI named githubnext/agentics explicitly

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

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

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

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